Not for publication or presentation · 2014. 1. 14. · Not for publication or presentation DRAFT AGENDA CIBMTR WORKING COMMITTEE FOR HEALTH POLICY AND PSYCHOSOCIAL ISSUES San Diego,

Not for publication or presentation

DRAFT AGENDA CIBMTR WORKING COMMITTEE FOR HEALTH POLICY AND PSYCHOSOCIAL ISSUES San Diego, California Friday, February 3, 2012, 12:15–2:15 pm Co-Chair: Steve Joffe, MD, MPH, Dana Farber Cancer Institute and Children’s Hospital, Boston, MA Phone: 617-632-5295; Fax: 617-632-2270; E-mail: [email protected] Co-Chair: Susan Parsons, MD, MRP, Tufts Medical Center, Boston, MA Phone: 617-636-1450; Fax: 617-636-6280; E-mail: [email protected] Statisticians: Anna Hassebroek, MPH, CIBMTR, Minneapolis, MN Phone: 612-884-8611; Fax: 612-884-8661; E-mail: [email protected] John Klein, PhD, CIBMTR, Milwaukee, WI Phone: 414-456-8379; Fax: 414-456-6530; E-mail: [email protected] Ruta Bajorunaite, PhD, CIBMTR, Milwaukee, WI Phone: 414-456-8687; Fax: 414-456-6520; E-mail: [email protected] Scientific Navneet Majhail, MD, MS, National Marrow Donor Program, Minneapolis, MN Director: Phone: 612-884-8676; Fax: 612-884-8549; E-mail: [email protected] 1. Introduction

Minutes from February 2011 meeting (Attachment 1) 2. Accrual summary (Attachment 2) 3. Published or submitted papers

a. HS06-02 Ballen KK, Klein JP, Pedersen TL, et al. Relationship of race/ethnicity and survival after single umbilical cord blood transplantation for adults and children with leukemia and myelodysplastic syndromes. Biol Blood Marrow Transplant, in press, available online 4 November 2011, doi:10.1016/j.bbmt.2011.10.040.

b. HS06-03 Majhail SM, Brazauskas R, Hassebroek A, et al. Outcomes of allogeneic hematopoietic cell transplantation for adolescent and young adults compared with children and older adults with acute myeloid leukemia. Biol Blood Marrow Transplant, in press, available online 29 October 2011, doi:10.1016/j.bbmt.2011.10.031.

4. Publications / abstracts from Health Services Research Program

a. Majhail NS, Murphy EA, Omondi NA, Robinett P, Gajewski JL, LeMaistre CF, Confer D, Rizzo JD. Allogeneic transplant physician and center capacity in the United States. Biol Blood Marrow Transplant 2011; 17(7): 956-961.

b. Denzen EM, Burton Santibañez ME, Moore H, Foley A, Gersten ID, Gurgol C, Majhail NS, Spellecy R, Horowitz MM, Murphy EA. Easy-to-read informed consent forms for hematopoietic cell transplant clinical trials. Biol Blood Marrow Transplant, in press, available online 30 July 2011, doi: 10.1016/j.bbmt.2011.07.022.

c. Majhail NS, Nayyar S, Santibañez ME, Murphy EA, Denzen EM. Racial disparities in hematopoietic cell transplantation in the United States. Bone Marrow Transplant, advance online publication 2011 Nov 7, doi: 10.1038/bmt.2011.214.

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d. Majhail NS, Murphy EA, Denzen EM, Ferguson SS, Anasetti C, Bracey A, Burns L, Champlin R, Hubbard N, Markowitz M, Maziarz RT, Medoff E, Neumann J, Schmit-Pokorny K, Weisdorf DJ, Yolin Raley DS, Chell J, Snyder EL. The National Marrow Donor Program’s symposium on hematopoietic cell transplantation in 2020: a health care resource and infrastructure assessment. Biol Blood Marrow Transplant, in press, available online 2011 Dec 14, doi:10.1016/j.bbmt.2011.10.004.

e. Omondi NA, Stickney Ferguson S, Majhail NS, Buchanan GR, Haight AE, Labotka RJ, Rizzo JD, Murphy EA. Barriers to clinical trial participation of African American and Black youth with sickle cell disease and their parents. In: Sickle cell disease: the next century: 5th annual sickle cell disease research and educational symposium & grant writing institute and annual national sickle cell disease scientific meeting. Am J Hematol 2011; 86(10): E1–E60.

f. Murphy EA, Schmit-Pokorny K, Sylvanus T, Lofthus ADK, Denzen E, Neumann J. Preparing for oncology patient needs: blood and marrow transplant nursing workforce system capacity initiative. Oncol Nurs Forum 2011; 38(2): E147.

5. Presentations at Tandem

a. HS07-02 Patient and family out-of-pocket costs of allogeneic hematopoietic cell transplantation (HCT): a pilot study Oral abstract: Session F – Supportive Care; Thursday, February 2nd 4:45–6:15 pm

b. HSR Identifying challenges to the future BMT nursing workforce: HSCT in 2020. Oral presentation: System Capacity Initiative; Friday, February 3rd 3:45–5:00 pm

c. HSR Costs of hospitalization for HCT in the US: a pilot study using a large national commercial payor database. Poster Session I; Wednesday, February 1st 6:45–7:45 pm

6. Studies in progress (Attachment 3)

a. HS09-01 Practice patterns in HCT for AML (N Majhail) (Attachment 4)

Protocol Development

b. HS11-01 Generalizability of BMT CTN 0201 results (N Khera/SJ Lee) (Attachment 5)


c. HS11-02 Comparison of length of stay among alternative graft sources (K Ballen) (Attachment 6)


d. HS10-01 HCT for adolescents/young adults with ALL (W Wood) (Attachment 7)

Data File Preparation

e. HS08-03 Estimating current burden/future trends in HCT survivors (N Majhail/B Virnig/K Kuntz) (Attachment 8)

Analysis

f. HS07-01 Description of transplant utilization, procedure patterns and patient characteristics (T Hahn/P McCarthy)

Manuscript Preparation

g. HS07-02 Financial impact of allogeneic HCT on patient and family (K Pederson/N Ormondi/H James/N Majhail)


h. HS08-01 Accreditation deficiencies C/T outcomes post-HCT (F Loberiza/ CF LeMaistre/P Warkentin/SJ Lee)


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Not for publication or presentation

6. Future / Proposed studies a. PROP1111-60 The impact of mandatory reporting of center-specific outcomes on patient

selection and center outcomes for allogeneic HCT in the US (N Majhail/JD Rizzo) (Attachment 9)

b. PROP1111-61 Rates of transplantation in urban vs. rural patients: are rural patients less likely to receive an allogeneic transplant? (Paulson/Seftel/Szwajcer) (Attachment 10)

c. PROP1111-63 Survival trends over time among white and black patients after unrelated donor HCT for acute leukemia and myelodysplastic syndromes (E Denzen/N Majhail) (Attachment 11)

7. Other business

Update on Health Services Research Program (N Majhail)

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Not for publication or presentation Attachment 1

MINUTES CIBMTR WORKING COMMITTEE FOR HEALTH SERVICES AND PSYCHOSOCIAL ISSUES Honolulu, Hawaii Sunday, February 20, 2011, 12:15 pm–2:15 pm Co-Chair: Steve Joffe, MD, MPH, Dana Farber Cancer Institute, Boston, MA Phone: 617-632-5295; Fax: 617-632-2270; E-mail: [email protected] Co-Chair: Susan Parsons, MD, MRP, Tufts Medical Center, Boston, MA Phone: 617-636-1450; Fax: 617-636-6280; E-mail: [email protected] Statisticians: Anna Hassebroek, MPH, CIBMTR, Minneapolis, MN Phone: 612-884-8611; Fax: 612-884-8661; E-mail: [email protected] John Klein, PhD, CIBMTR, Milwaukee, WI Phone: 414-456-8379; Fax: 414-456-6530; E-mail: [email protected] Ruta Bajorunaite, PhD, CIBMTR, Milwaukee, WI Phone: 414-456-8687; Fax: 414-456-6520; E-mail: [email protected] Scientific Director: Navneet Majhail, MD, MS, University of Minnesota, Minneapolis, MN Phone: 612-624-6982; Fax: 612-625-6919; E-mail: [email protected]

1. Introduction

The meeting was called to order. The minutes of the 2010 Tandem meeting were approved by the committee.

2. Accrual Summary

The accrual tables were reviewed. In the past, many of the socio-demographic variables have had large numbers of missing data, making studies in this committee challenging. However, since the implementation of the SCTOD, there are fewer numbers of patients missing data for variables such as education, race/ethnicity, etc. In addition, ZIP code information is now available for all transplants. Income is still largely missing; the ZIP code data allows for the approximation of patient income.

3. Published or submitted papers

a. HS05-02 Bravo-Biosca A, Schneider F. Consolidation, volume and outcomes in leukemia treatment. Submitted to Journal of Health Economics.

b. HS06-01/MM06-03 Hari PN, Majhail NS, Zhang M-J, Hassebroek A, Siddiqui F, Ballen K, Bashey A, Bird J, Freytes CO, Gibson J, Hale G, Holmberg L, Kamble R, Kyle RA, Lazarus HM, LeMaistre CF, Loberiza FR, Maiolino A, McCarthy PL, Milone G, Omondi N, Reece DE, Seftel M, Trigg M, Vesole D, Weiss B, Wiernik P, Lee SJ, Rizzo JD, Mehta P. Race and outcomes of autologous hematopoietic cell transplantation for multiple myeloma. Biol Blood Marrow Transplant 2010 Mar; 16(3):395-402.

c. HS06-06 Joshua TV, Rizzo JD, Zhang M-J, Hari PN, Kurian S, Pasquini M, Majhail NS, Lee SJ, Horowitz MM. Access to hematopoietic stem cell transplantation effect of race and gender. Cancer 2010 Jul 15; 116(14):3469-76.

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d. HS08-02 Loberiza FR Jr., Lee SJ, Klein JP, Hassebroek A, Dehn JG, Frangoul HA, Hahn T, Hale G, Lazarus HM, LeMaistre CF, Maziarz RT, Rizzo JD, Majhail NS. Outcomes of hematological malignancies after unrelated donor hematopoietic-cell transplantation according to place of residence. Biol Blood Marrow Transplant 2010 Mar; 16(3):368-75.

e. HS08-04 Howard D, Kenline C, Gajewski J, Hale G, Hassebroek A, Hayes-Lattin B, Horowitz MM, Lazarus H, LeMaistre CF, Maziarz R, McCarthy P, Parsons S, Rizzo JD, Szwajcer D, Majhail N. Is comparative effectiveness research effective? Abandonment of high dose chemotherapy/hematopoietic cell transplants for breast cancer. Submitted to Health Services Research.

4. Publications from Health Services Research Program

a. Murphy E, Ferguson SS, Omondi NA, Getzendaner L, Gajewski JL, Goldstein G, Wingard JR, Rizzo JD, Majhail NS. National Marrow Donor Program’s symposium on patient advocacy in cellular transplant therapy: addressing barriers to hematopoietic cell transplantation. Biol Blood Marrow Transplant 2010; 16:147-56.

b. Majhail NS, Omondi NA, Denzen E, Murphy EA, Rizzo JD. Access to hematopoietic-cell transplantation in the United States. Biol Blood Marrow Transplant 2010; 16: 1070-75.

c. Omondi NA, Denzen E, Jacobson D, Payton T, Pederson K, Murphy EA. Evaluating patient satisfaction with the Office of Patient Advocacy. Journal of Cancer Education 2010 (in press).

d. Majhail NS, Murphy EA, Omondi NA, Robinett P, Gajewski JL, LeMaistre CF, Confer D, Rizzo JD. Allogeneic transplant physician and center capacity in the United States. Submitted to Biology of Blood and Marrow Transplantation. Q. How are the activities of the HP working committee different from those of the HSR? A. Any studies that come from the database will go through the working committee. Any

projects that need data/efforts beyond the database will go through the HSR. The chairs are also included in HSR activities and therefore can advise on which format a particular study should go through. The working committee and HSR are meant to compliment each other; the HSR will have separate hours for prioritizing activities.

5. Studies in Progress

a. HS07-02 Financial impact of allogeneic HCT on patient and family (K Pederson/N Omondi/H James/N Majhail) This study is an example of the type of project that would be done through the HSR in the future. The study involves collection of data at three sites on out of pocket costs to families as a result of transplantation. It was a pilot study to test the feasibility of collecting the data and to test the survey instrument. Accrual has been completed and the data is being put together. After the study is complete, the survey instrument will be made available for public use.

b. HS09-01 Practice patterns in hematopoietic cell transplantation for acute leukemias (N Majhail/JD Rizzo) The protocol is being developed and will be circulated to the committee in the next few months.

c. HS08-01 Accreditation deficiencies and survival outcomes post-HCT (F Loberiza/CF

LeMaistre/P Warkentin/SJ Lee) The protocol is being developed and will be worked on over the next few months.

d. HS10-01 HSCT for adolescents/young adults with ALL (W Wood)

The protocol has been circulated to the writing committee and the PI is working on responding to comments. The data file will be prepared later in the calendar year.

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e. HS06-03 Survival Trends among Adolescent and Young Adult (AYA) Recipients of Sibling

Allogeneic Hematopoietic Stem Cell Transplantation for the Treatment of Leukemia or Lymphoma (B Hayes-Lattin) The analysis is complete and the manuscript is being prepared. The draft manuscript will be circulated to the writing committee this spring.

f. HS08-03 Estimating current burden/future trends in HCT survivors (N Majhail/B Virnig/K

Kuntz) The analysis is ongoing and the results will be circulated to the writing committee by summer.

g. HS06-02 Comparison of cord blood utilization and transplant outcomes among different

racial/ethnic groups undergoing cord blood transplantation (K Ballen) The manuscript will be submitted by the end of April. Hispanic and White outcomes are comparable; Black do worse. However, if Black patients have good cell counts and their HLA matching is good, then they also have similar outcomes to Hispanic and White patients.

h. HS07-01 Description of transplant utilization, procedure patterns and patient characteristics (T

Hahn/P McCarthy) The analysis is complete and the manuscript is being prepared. There were two abstracts presented at ASH 2010, one for allogeneic and autologous transplants which show that post-transplant outcomes generally have improved over time.

6. Planning for Future Studies

Navneet Majhail, Brent Logan and Ruta Bajorunaite reviewed ongoing activities in the CIBMTR that address issues related to center analyses and center-level effects, which may be of interest to the committee when planning future studies. Center Survey (HSR project) Navneet Majhail summarized the survey, which will go out to centers during Summer 2011. The survey will collect data on center characteristics, transplant provider and delivery of care. The hope is to administer the survey every two years and use TED-level data to see how these factors affect outcomes post-transplant. The HSR is applying for funding to provide incentive to centers to participate in the survey. Collaboration with FACT is also ongoing to determine if there are some things that FACT can contribute to the data. Outcomes will look at early endpoints such as 100-day and 1-year survival. Q. How do you see this information being used? Will it be used to address staffing issues or whether

certain centers are not performing up to some standard? A. There is no plan to identify individual centers. The idea is to hopefully identify some areas of

care that centers could modify to improve patient outcomes. Q. Who will complete the survey? A. The survey will go to the center director but that person may pass it along to center

administrators. Center Specific Analysis Brent Logan gave a review on the current analysis CIBMTR does to look at how individual centers are performing. This consists of a risk-adjusted analysis of one-year survival. Historically this included only unrelated transplants but is being expanded to the related donors due to the SCTOD.

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All centers are included provided they have sufficient follow-up. The analysis uses risk factors collected on the TED forms and compares the observed survival and expected survival for a particular center. This analysis suggests that there is a difference in outcomes for different centers and the HSR survey is a good way to attempt to describe what is causing the variability. Q. Is there a plan for distributing this center information to the public? A. The data is available now on the HRSA website. Q. Is there a plan to collect data on who is accessing the website? It would be interesting to know if

patients are using the data and whether it affects their decisions on where to get transplanted. Statistical Methodology Ruta Bajorunaite spoke about the statistical methodology that should be considered when studying center characteristics. Center characteristics can be looked at by focusing on overall survival (Cox models or pseudo-value approach) or by looking at survival correlation. Because centers come and go from reporting, it is important to look at short-term outcomes.

7. Future/Proposed Studies

a. PROP0910-01 Is outcome of HLA full-matched allogeneic HSCT different between various ethnic populations (C Ustun/E Warlick/KS Baker) C. Ustun presented a summary of the proposal which would investigate whether ethnicity remains a risk factor that impacts HSCT outcomes and complications after allogeneic HSCT when the donor and recipient are fully HLA-matched by high resolution typing. Previous studies indicated outcomes were different for minority patients; however, this was before high resolution typing was available. Donor ethnicity will also be evaluated to determine impact on outcomes. The outcomes of interest are TRM, overall- and disease-free survival. Q. Are there enough patients in the minority populations to do the study? A. A power calculation should be done to determine that. Comment: How is this different from the Baker study? Response: The Baker study did a subset analysis of patients with high resolution typing (any

number of matches) and obtained similar results. There were not enough patients to evaluate patients who were fully matched with high resolution typing.

Comment: It would be interesting to reframe the study so that it could dissect whether the

differences found are due to actual biological differences or socioeconomic differences.

b. PROP1110-07 Generalizability of BMTCTN 0201 results: prognostic and outcome differences

between participants and nonparticipants (N Khera/S Lee) Nandita Khera presented this proposal which aims to evaluate the generalizability of results of the BMTCTN 0201 clinical trial to the entire population of patients to determine the optimal application of results. This study will use TED level data to examine differences between the characteristics and transplant outcomes of participants with those of non-trial patients. Comparison of outcomes such as overall survival, acute and chronic GVHD and relapse, TRM and disease-free survival will be done after the primary analysis from the trial is completed. Q. What if you find the trial results are not generalizable?

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A. If results are not generalizable, the next step would be to identify groups who were not captured in the trial for future studies.

Q. Will donor issues be available for study? A. There is some information available on donors, although this information will need to be

considered carefully. c. PROP1210-20 Comparison of length of stay among alternative graft sources: single and double

cord blood, matched unrelated donor, other related donors (K Ballen) Karen Ballen summarized this proposal. The aim of the study would be to determine the length of stay as a surrogate of cost of hospitalization in the first 100-days post-transplant in recipients of cord blood (single or double), matched unrelated donors (bone marrow or PBSC) and mismatched related donors; to determine the risk factors for prolonged length of stay; and to determine if length of stay is decreasing over time. The study population will include acute leukemia patients in remission who were transplanted at US centers. The primary outcome will be to describe the number of hospital days in the first 100 days post-transplant and will be done for each graft type. The data shows that length of stay is more complete after 2008 due to SCTOD required reporting. Comment: The length of stay will be different for pediatric vs. adult patients; analysis should

stratify for that. Another option is to limit to adults so that there are no single cord transplants.

Q. Will you exclude patients that died early? A. This will need to be discussed to determine the best way to statistically analyze this data. Q. Are you planning to capture the patients that are readmitted? A. The forms do not collect that data. If the patient was readmitted in the first 100 days, those

days would be included in the total number of inpatient days. Comment: Based on preliminary tables, adults receiving single or double cord blood transplants

seem to have longer length of stay than BM or PBSC. We should include time to engraftment as an outcome to see if engraftment explains part or all of that difference.

Comment: Length of stay may be center preference. Comment: How will we interpret the results? Longer length of stay may be less expensive up

front but longer up-front treatment may affect long term outcomes and be cheaper in the long term?

d. PROP1210-47 Incidence of post-transplant complications according to payer status in patients

receiving allogeneic HSCT for AML (K Kennedy/V Adams/A Lawson/J Talbert/B Motheral/D Howard) Kenneth Kennedy presented this proposal. The primary objective is to compare rates of post-transplant grade II-IV GVHD between Medicaid and private insurance patients. Secondary objectives include infection frequency, overall survival at 1-year and resource utilization such as hospital length of stay. The patient population consists of adults with AML who received an allogeneic transplant between 2000-2010.

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Comment: Is payer status the only factor driving prophylaxis use or is it something else such as patient compliance or center practice?

Comment: Some centers know before the patient leaves the hospital what type of drug they will

need and whether that drug will be covered by the patient’s insurance. Comment: Patient adherence will be correlated to insurance type due to socioeconomic status. Comment: Limit to AML in complete remission so the population is more homogeneous. Comment: Medicaid has many different types of payers whereas Medicare is only one payer.

The population could be limited to Medicare patients to obtain get around issues about differences in payment.

Comment: One option would be to look at private insurance in two groups: good SES with

private insurance and poor SES with private insurance. This may separate out patients that may be self-pay rather than insurance.

Comment: The study population could be expanded to other diseases because aGVHD is the

outcome of interest. Comment: T-cell depleted patients should be excluded from the study.

8. Other Business

N Majhail updated the committee on the Health Services Research program.

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Accrual Summary for Health Services/Psychosocial Issues Working Committee

Characteristics of recipients of allogeneic transplants reported to the CIBMTR through November 2011.

TED** CRF

Characteristics N (%) N (%)

Number of Patients 168,058 82,329Number of Centers 573 501Age, years Median (range) 33 (<1-83) 30 (<1-82) < 10 25,784 (15) 14,283 (17) 10-19 24,103 (14) 13,263 (16) 20-29 25,066 (15) 13,270 (16) 30-39 28,224 (17) 14,253 (17) 40-49 30,312 (18) 13,790 (17) 50-59 23,476 (14) 9641 (12) ≥ 60 10,757 ( 6) 3814 ( 5) Missing 336 (<1) 15 (<1)Male 98,587 (59) 48,249 (59)Recipient Race/Ethnicity Non-Hispanic White 109,841 (65) 64,521 (78) African-American 6736 ( 4) 3626 ( 4) Asian/Pacific Islander 12,408 ( 7) 6260 ( 8) Hispanic 8884 ( 5) 4976 ( 6) Native American 315 (<1) 189 (<1) Other 13,995 ( 8) 2320 ( 3) Missing 15,879 ( 9) 437 ( 1)Disease Acute leukemia 83,409 (50) 39,594 (48) CML 26,808 (16) 14,715 (18) MDS 15,549 ( 9) 6857 ( 8) Non-Hodgkin lymphoma 11,963 ( 7) 4789 ( 6) Hodgkin lymphoma 1247 ( 1) 445 ( 1) Multiple myeloma/Plasma cell disorder 3106 ( 2) 1315 ( 2) Solid tumor 1102 ( 1) 487 ( 1) Breast cancer 180 90 Severe aplastic anemia 10,875 ( 6) 6287 ( 8) Inherited abnormalities of erythrocytes 6263 ( 4) 3622 ( 4) Metabolic and Immune disorders 6832 ( 4) 3821 ( 5) Other 314 (<1) 108 (<1) Missing 410 199 (<1)

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Continued.

TED CRFCharacteristics N (%) N (%)

Graft Type Bone marrow 93,216 (55) 53,801 (65) Peripheral blood 65,713 (39) 23,127 (28) Umbilical cord 9129 ( 5) 5401 ( 7)Donor Type HLA-identical sibling 94,967 (57) 41,491 (50) Identical twin 1682 ( 1) 943 ( 1) Other relative 12,264 ( 7) 5574 ( 7) Unrelated donor 56,020 (33) 32,982 (40) Missing 3125 ( 2) 1339 ( 2)Year of transplant < 1985 4617 ( 3) 4372 ( 5) 1985-1989 10,408 ( 6) 9485 (12) 1990-1994 22,454 (13) 14,700 (18) 1995-1999 35,207 (21) 16,738 (20) 2000-2004 40,508 (24) 16,798 (20) 2005-2009 40,156 (24) 17,930 (22) 2010-2011 14,708 ( 9) 2306 ( 3)Education No primary education 16 (<1) High school degree or lower 6091 ( 7) Some college 2454 ( 3) Bachelors degree or masters degree program 3155 ( 4) Advanced degree 983 ( 1) Pt < 18 yrs old 24,777 (30) Missing 44,853 (54)Health Insurance No insurance 1786 ( 2) Medicaid 3508 ( 4) Medicare 991 ( 1) Disability insurance 210 HMO 1258 ( 2) Private or group health insurance 10,692 (13) National health insurance 13,816 (17) VA/military 391 (<1) Other 2458 ( 3) Missing 47,219 (57)

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Continued.

TED CRFCharacteristics N (%) N (%)

Occupation Professional, technical 5163 ( 6) Manager, administrator, proprietor 2055 ( 2) Clerical 2139 ( 3) Sales 1422 ( 2) Service occupation 1844 ( 2) Skilled crafts 2313 ( 3) Equipment or vehicle operator 1007 ( 1) Laborer 1495 ( 2) Farmer 431 ( 1) Military 329 (<1) Homemaker 2046 ( 2) Student 5384 ( 7) Under school age 1340 ( 2) Not previously employed 522 ( 1) Other 6925 ( 8) Missing 47,914 (58)Income < $20,000 141 (<1) $20,000-$39,999 176 (<1) $40,000-$59,999 137 (<1) $60,000-$79,999 91 (<1) ≥ $80,000 156 (<1) Recipient declines to provide informatio 170 Missing 81,458 (99)

Abbreviations:MDS=Myelodysplastic Syndrome; CNS=Central Nervous System; HMO=Health Maintenance Organization; VA=Veteran's Affairs; HLA=Human Leukocyte Antigen; GVHD=Graft vs host disease; T-del=T-cell depletion; ATG=Anti-thymocyte globulin; TBI=Total body irradiation. * Only first transplants are included in this accrual. ** TED = Transplant Essential Data forms completed with CIBMTR; CRF = Complete Report Forms completed with CIBMTR.

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Characteristics of recipients of allogeneic transplants with CRF data reported to the CIBMTR from

January 2008 – November 2011.

Characteristics N (%)

Number of Patients 9411 Number of Centers 227 Education No primary education 14 (<1) High school degree or lower 2056 (22) Some college 858 ( 9) Bachelors degree or masters degree program 1418 (15) Advanced degree 275 ( 3) Pt < 18 yrs old 2464 (26) Missing 2326 (25) Health Insurance No insurance 467 ( 5) Medicaid 1590 (17) Medicare 596 ( 6) Disability insurance 144 ( 2) Private or group health insurance 4562 (48) National health insurance 941 (10) VA/military 110 ( 1) Other 276 ( 3) Missing 725 ( 8)

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Continued.


Occupation Professional, technical 1498 (16) Manager, administrator, proprietor 718 ( 8) Clerical 520 ( 6) Sales 390 ( 4) Service occupation 524 ( 6) Skilled crafts 614 ( 7) Equipment or vehicle operator 262 ( 3) Laborer 414 ( 4) Farmer 70 ( 1) Military 56 ( 1) Homemaker 268 ( 3) Student 1771 (19) Under school age 926 (10) Not previously employed 196 ( 2) Other 371 ( 4) Missing 813 ( 9) Income < $20,000 67 ( 1) $20,000-$39,999 79 ( 1) $40,000-$59,999 56 ( 1) $60,000-$79,999 48 ( 1) ≥ $80,000 78 ( 1) Recipient declines to provide information 163 ( 2) Missing 8920 (95)

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Characteristics of recipients of autologous transplants reported to the CIBMTR through November 2011.

TED CRF


Number of Patients 146,301 32,920

Number of Centers 531 335

Age, years

Median (range) 50 (<1-89) 48 (<1-83)

< 10 6835 ( 5) 1808 ( 5)

10-19 5635 ( 4) 1407 ( 4)

20-29 11,439 ( 8) 2365 ( 7)

30-39 18,653 (13) 4704 (14)

40-49 32,091 (22) 8146 (25)

50-59 40,544 (28) 8521 (26)

≥ 60 30,923 (21) 5958 (18)

Missing 181 (<1) 11 (<1)

Male 73,551 (50) 14,885 (45)

Recipient Race/Ethnicity

Non-Hispanic White 100,121 (68) 26,541 (81)

African-American 10,764 ( 7) 2558 ( 8)

Asian/Pacific Islander 2861 ( 2) 639 ( 2)

Hispanic 7116 ( 5) 2088 ( 6)

Native American 246 (<1) 88 (<1)

Other 12,897 ( 9) 688 ( 2)

Missing 12,296 ( 8) 318 ( 1)

Disease

Acute leukemia 9163 ( 6) 2464 ( 7)

CML 604 (<1) 248 ( 1)

MDS 205 (<1) 33 (<1)

Non-Hodgkin lymphoma 40,790 (28) 7783 (24)

Hodgkin lymphoma 16,583 (11) 2627 ( 8)

Multiple myeloma/plasma cell disorder 43,163 (30) 7846 (24)

Solid tumor 13,394 ( 9) 3800 (12)

Breast cancer 21,435 (15) 7722 (23)

Severe aplastic anemia 10 3 (<1)

Other 746 (<1) 130 (<1)

Missing 208 (<1) 264 ( 1)

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Continued.

TED CRF


Graft Type

Bone marrow 15,299 (10) 5678 (17)

Peripheral blood 131,002 (90) 27,242 (83)

Year of transplant

< 1985 96 (<1) 2 (<1)

1985-1989 1591 ( 1) 641 ( 2)

1990-1994 17,809 (12) 7308 (22)

1995-1999 39,426 (27) 12,371 (38)

2000-2004 34,372 (23) 5122 (16)

2005-2009 37,276 (25) 7149 (22)

2010-2011 15,731 (11) 327 ( 1)

Education

No primary education 1 (<1)

High school degree or lower 4324 (13)

Some college 2360 ( 7)

Bachelors degree or masters degree program 3175 (10)

Advanced degree 1280 ( 4)

Pt < 18 yrs old 2841 ( 9)

Missing 18,939 (58)

Health Insurance

No insurance 539 ( 2)

Medicaid 2125 ( 6)

Medicare 2032 ( 6)

Disability insurance 126 (<1)

HMO 2938 ( 9)

Private or group health insurance 13,218 (40)

National health insurance 1606 ( 5)

VA/military 493 ( 1)

Other 1963 ( 6)

Missing 7880 (24)

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Continued.

TED CRF


Occupation

Professional, technical 4719 (14)

Manager, administrator, proprietor 1944 ( 6)

Clerical 2221 ( 7)

Sales 1087 ( 3)

Service occupation 1384 ( 4)

Skilled crafts 1597 ( 5)

Equipment or vehicle operator 697 ( 2)

Laborer 1154 ( 4)

Farmer 298 ( 1)

Military 167 ( 1)

Homemaker 1981 ( 6)

Student 465 ( 1)

Under school age 164 (<1)

Not previously employed 148 (<1)

Other 2824 ( 9)

Missing 12,070 (37)

Income

< $20,000 270 ( 1)

$20,000-$39,999 266 ( 1)

$40,000-$59,999 274 ( 1)

$60,000-$79,999 147 (<1)

≥ $80,000 335 ( 1)

Recipient declines to provide information 92 (<1)

Missing 31,536 (96) Abbreviations: MDS=Myelodysplastic Syndrome; CNS=Central Nervous System; HMO=Health Maintenance Organization; VA=Veteran's Affairs; HLA=Human Leukocyte Antigen; GVHD=Graft vs host disease; T-del=T-cell depletion; ATG=Anti-thymocyte globulin; TBI=Total body irradiation. * Only first transplants are included in this accrual. ** TED = Transplant Essential Data forms completed with CIBMTR; CRF = Complete Report Forms completed with CIBMTR.

17



Characteristics of recipients of autologous transplants with CRF data reported to the CIBMTR from

January 2008 – November 2011.


Number of Patients 3472 Number of Centers 159 Education No primary education 1 (<1) High school degree or lower 1031 (30) Some college 477 (14) Bachelors degree or masters degree program 670 (19) Advanced degree 119 ( 3) Pt < 18 yrs old 287 ( 8) Missing 887 (26) Health Insurance No insurance 98 ( 3) Medicaid 372 (11) Medicare 591 (17) Disability insurance 55 ( 2) Private or group health insurance 1881 (54) National health insurance 111 ( 3) VA/military 64 ( 2) Other 79 ( 2) Missing 221 ( 6)

18



Continued.


Occupation Professional, technical 694 (20) Manager, administrator, proprietor 343 (10) Clerical 253 ( 7) Sales 179 ( 5) Service occupation 283 ( 8) Skilled crafts 318 ( 9) Equipment or vehicle operator 140 ( 4) Laborer 199 ( 6) Farmer 42 ( 1) Military 37 ( 1) Homemaker 123 ( 4) Student 210 ( 6) Under school age 124 ( 4) Not previously employed 58 ( 2) Other 151 ( 4) Missing 318 ( 9) Income < $20,000 43 ( 1) $20,000-$39,999 51 ( 1) $40,000-$59,999 56 ( 2) $60,000-$79,999 33 ( 1) ≥ $80,000 57 ( 2) Recipient declines to provide information 75 ( 2) Missing 3157 (91)

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TO: Health Policy and Psychosocial Issues Working Committee Members FROM: Navneet Majhail, MD, MS; Scientific Director for the Health Policy WC RE: Studies in Progress Summary HS05-02: Consolidation, volume and outcomes in leukemia treatment (A Bravo-Biosca / F Schneider): The purpose of this study is to examine the effect of consolidation on survival by empirically analyzing the causal nature of the volume-outcome relationship. The manuscript was submitted to the Journal of Health Economics. HS06-02: Comparison of cord blood utilization and transplant outcomes among different racial/ethnic groups undergoing hematopoietic cell transplantation (HCT) (K Ballen): The objective of this study is to determine if the clinical outcomes of cord blood transplantation for White patients is comparable to the outcomes in Black and Hispanic patients. The study was an oral presentation at the ASH meeting in December 2010; the manuscript has been accepted for publication in BBMT. HS06-03: Survival trends among adolescent and young adult recipients of sibling allogeneic hematopoietic cell transplantation (HCT) for the treatment of acute myelogenous leukemia (AML) (B Hayes-Lattin): Using data submitted to the CIBMTR, this analysis is comparing outcomes of AYA with children and older adult recipients of allogeneic HCT for acute myeloid leukemia (AML) to determine whether age-related differences in outcomes exist in HCT. The manuscript has been accepted for publication in BBMT. HS07-01: Description of transplantation utilization, procedure patterns and patient characteristics (P McCarthy / T Hahn): This study assessed whether overall survival at 100 days and one year changed during the time period of 1995-2005. Two abstracts were accepted as poster presentations at the ASH meeting in December 2010; the manuscripts are currently being prepared. HS07-02: The financial impact of allogeneic stem cell transplantation (HCT) on patient and family (K Pederson / N Majhail): This is a pilot study that aims to describe the out-of-pocket costs and income changes that may result from HCT. This information could potential help patients and their caregivers have a clearer picture of these costs and develop a financial plan. Accrual of patients has been completed and the manuscript is being prepared. HS08-01: Accreditation deficiencies and survival outcomes post hematopoietic cell transplantation (HCT) (F Loberiza): This study examined the association between accreditation deficiencies on survival outcomes after HCT from clinical transplant programs in the US. The analysis is complete and the manuscript is being written. HS08-03: Estimating current burden/future trends in the number of hematopoietic cell transplant (HCT) survivors in the USA (N Majhail): This study will estimate the present overall number of HCT survivors in the US. Analysis is complete and a draft manuscript is under preparation.

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HS08-04: Autologous hematopoietic cell transplantation (HCT) for breast cancer (D Howard): This study used patient-level data from the CIBMTR to examine dis-adoption of high dose chemotherapy followed by autologous blood and marrow transplantation as a treatment for breast cancer following the release of negative clinical trials results in early 1999. The manuscript was published in the December 2011 issue of Health Services Research. HS09-01: Practice patterns in hematopoietic cell transplantation (HCT) for acute myelogenous leukemia (AML) (N Majhail): This study will describe practice variations in the use of HCT for AML and ALL in the US from 2008-09. A draft protocol is currently being reviewed. HS10-01: Outcomes of HSCT for adolescents and young adults with ALL (W Wood / N Majhail / T Shea / SJ Lee): This study will compare changes over time in OS and TRM between adolescent/young adults and an older and younger cohort, with ALL in first or second complete remission. The data file is currently being prepared and analysis should be complete by June 2012. HS11-01: Generalizability of BMT CTN 0201 (N Khera/SJ Lee): This study will evaluate whether there are differences in patient characteristics or transplant outcomes between patients treated on the BMT CTN 0201 trail and patients from the entire cohort of patients transplanted during the study time period. The protocol is currently under review. HS11-02: Comparison of length of stay among alternative graft sources (K Ballen): This protocol will study the length of stay in the first 100 days post-transplant to evaluate any differences between different graft sources, including single and double cord blood, matched unrelated donor bone marrow or peripheral blood and other related (non-HLA identical sibling) transplants. A protocol is currently under review.

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CIBMTR HS09-01

CENTER PRACTICE VARIATION IN MYELOABLATIVE ALLOGENEIC HEMATOPOIETIC

CELL TRANSPLANTATION FOR ACUTE LEUKEMIA IN THE UNITED STATES

DRAFT PROTOCOL Study Chairs: Navneet Majhail, MD, MS NMDP/CIBMTR 3001 Broadway Street NE, Suite 100 Minneapolis, MN 55413 Telephone: 612-884-8676 Fax: 612-884-8549 E-mail: [email protected] J. Douglas Rizzo, MD MS CIBMTR Froedtert and the Medical College of Wisconsin Clinical Cancer Center 9200 W. Wisconsin Avenue Suite C5500 Milwaukee, WI 53226 Telephone: (414) 805-0700 Fax: (414) 805-0714 E-mail: [email protected] Susan Parsons, MD, MRP Tufts Medical Center 800 Washington St, #63 Boston, MA 02111 Telephone: 617-636-1450 Fax: 617-636-6280 E-mail: [email protected] Steve Joffe, MD, MPH Dana Farber Cancer Institute 44 Binney St. Boston, MA 02115 Telephone: 617-632-5295 Fax: 617-632-2270

E-mail: [email protected]

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Study Statistician: Anna Hassebroek, MPH CIBMTR 3001 Broadway Street NE, Suite 110 Minneapolis, MN 55413 Telephone: 612-884-8611 Fax: 612-884-8661 E-mail: [email protected] Scientific Director: Navneet Majhail, MD, MS NMDP/CIBMTR 3001 Broadway Street NE, Suite 100 Minneapolis, MN 55413 Telephone: 612-884-8676 Fax: 612-884-8549 E-mail: [email protected] Working Committee Chairs: Susan Parsons, MD, MRP Tufts Medical Center 800 Washington St, #63 Boston, MA 02111 Telephone: 617-636-1450 Fax: 617-636-6280 E-mail: [email protected] Steve Joffe, MD, MPH Dana Farber Cancer Institute 44 Binney St. Boston, MA 02115 Telephone: 617-632-5295 Fax: 617-632-2270


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1.0 SPECIFIC AIMS: There exists significant practice variation in hematopoietic cell transplantation (HCT).1-3 We hypothesize that practice variation across centers does not impact patient outcomes after HCT and hence, similar patients have comparable outcomes when transplanted at different transplant centers despite major differences in center practices. The primary objectives of this study are: 1.1 To describe practice variation among transplant centers in United States (US) for adult

patients receiving allogeneic HCT for acute leukemia (acute myeloid leukemia [AML] and acute lymphoblastic leukemia [ALL]).

1.2 To evaluate whether practice variation among transplant centers influences 1-year overall survival among adult patients receiving allogeneic HCT for acute leukemia in first or second complete remission (CR1/CR2).

The secondary objectives of this study are: 1.3 To evaluate whether practice variation among transplant centers influences 1-year

cumulative incidence of non-relapse mortality (NRM) and relapse for patients receiving allogeneic HCT for acute leukemia in CR1/CR2.

1.4 To evaluate whether practice variation among transplant centers influences 100-day overall survival, and cumulative incidence of 100- day NRM and relapse in this population.

2.0 SCIENTIFIC JUSTIFICATION:

Practice variation in medicine There can be wide variations in the intensity and quality of care provided to different populations within a given geographic area. Wenneberg attributes variation in utilization of health care to four factors: illness rate, the patients decision to contact a physician, the physicians diagnostic decisions and the physicians treatment decisions.4 He has also introduced the concept of ‘practice style’, which reflects physician beliefs about the efficacy and appropriateness of alternative forms of care.5 The mix of physicians with different practice styles varies between areas and can lead to variations in utilization of health care between those areas. In general, it can be expected that variability is low when a disease is easy to diagnose, and when few alternative treatment options exist. Alternatively, if the indications for treatment are not very clear, or if several alternative types of treatment are possible, then greater variation can be expected.6 Practice variation in HCT Because of its complexity, the paucity of definitive outcomes data from randomized clinical trials and the resultant lack of agreement among transplant physicians, practice variation in HCT can be expected. Figure 1 shows a conceptual model of practice variation in transplantation. Practice variation can occur at various levels – both between/across and within centers. For the purpose of this study, we are most interested in evaluating practice variation across centers. The literature has a few examples of studies that highlight practice variation in HCT. Lee et al surveyed transplant physicians and found significant variations and heterogeneity in general transplant practices worldwide.2 They concluded that local preferences, referral patterns or biases likely result in similar patients being offered different transplant and treatment procedures. In a followup study, they also showed that there was significant variation in supportive care practices among transplant physicians.1

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Figure 1: Conceptual model of practice variation in allogeneic HCT

In addition to physician practices, HCT center characteristics (‘center effects’) can impact the organization and delivery of care after transplantation and have the potential to impact overall patient outcomes. Loberiza et al surveyed 163 US HCT centers for their characteristics and evaluated their association with mortality at 100 days and 1 year after autologous and HLA-identical sibling donor transplantation.3 They again demonstrated differences among center infrastructure and characteristics. Furthermore, they also showed an impact of center effects on transplant outcomes. Among recipients of HLA matched sibling allografts, HCT at centers with higher patient-per-physician ratio and at centers where physicians answered calls after office hours (vs. non-physicians) was associated with a lower risk of overall mortality at 1-year after transplantation. However, these center effects were weaker for autologous HCT. The study concluded that greater physician involvement in patient care is important in producing favorable outcomes after HCT. The Center Specific Outcomes Analysis, that is conducted by the CIBMTR in response to HRSA SCTOD contract requirements, also provides evidence that center effects can impact survival after allogeneic HCT. This analysis provides risk-adjusted analysis of 1-year survival for patients receiving allogeneic HCT at US centers and provides a comparison of a given centers observed survival with their risk-adjusted predicted survival. Among the 157 centers included in the 2010 analysis, the observed 1-year survival was no different than the expected survival for the majority

25


of centers. However, there were 13 under performing and 11 over performing centers with survival significantly below and above the predicted survival, respectively. Acute leukemia as a disease model to study practice variation in HCT AML and ALL are the most common indications for allogeneic HCT,7 and are diseases where indications for HCT have been best described. However, there are still many areas of controversy regarding the use of HCT. These include, but are not limited to, indications for transplantation, the timing of transplantation, optimal patient selection, optimal graft source, and optimal regimens for conditioning therapy and graft-versus-host disease (GVHD) prophylaxis. There are some areas of general consensus based on the results of large observational studies and clinical trials;8-10 for instance, allogeneic HCT in CR1 is recommended for AML and ALL with poor-risk disease and allogeneic HCT is recommended for all adult patients with AML and ALL in CR2. Study rationale and limitations We hypothesize that practice variation among transplant centers in HCT does not impact patient outcomes and hence, similar patients have comparable outcomes when transplanted at different centers despite major differences in center practices. This analysis will use existing data collected by the CIBMTR to compare survival and other patient outcomes based on center practices for patients receiving allogeneic HCT for acute leukemia using sibling or unrelated donors. Patient outcomes will be evaluated at day 100 and at 1 year. These time points have the potential to be most impacted by center practices. Center practice variation may also impact longer term survival, but it would be challenging to differentiate center specific effects from influence of other non-center factors (e.g. primary source of long-term care, ability to travel back to transplant center). We will restrict our study to transplants performed between 2008 and 2010. This will allow us to take advantage of universal reporting of all allogeneic HCT in the US under the purview of the Stem Cell Therapeutic Act. This study will: (1) Describe practice variation across centers for patients transplanted for AML and ALL (any disease stage), and (2) Will evaluate practice variation across centers as a predictor of transplant outcomes among patients transplanted for AML or ALL in CR1/CR2. Some limitations of this analysis have to be considered given the use of retrospective data from the CIBMTR observational registry. For instance, we will not be able to account for individual physician preferences. We will not be going back to centers to collect data on infrastructure and practices. We will not be able to identify patients enrolled on clinical trials other than through the BMT CTN; practice variation may be the result of innovative research in HCT for acute leukemia. Also, as discussed above, both patient and provider/center level factors can contribute to practice variation and our study will not be able to account for patient factors and preferences that may be contributing to practice variation. Finally, we propose using registration (TED) level data for this study in order to capture all allogeneic HCT in the US. However, this will limit availability of more detailed information for certain variables of interest (e.g. cytogenetics at diagnosis). We will have to limit our study to centers that have transplanted an adequate number of patients (e.g., ≥ 10 patients during the study period) to describe practice variation; hence, our study will be limited to larger centers and our findings may not be generalizable to all transplant centers in the US.

3.0 PATIENT ELIGIBILITY CRITERIA:

Registration (TED) level data will be utilized for this study. This study will include the following patients:

Allogeneic HCT for AML or ALL reported to the CIBMTR from 2008 to 2010.

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HCT using myeloablative and non-myeloablative/reduced-intensity conditioning regimens.

HCT performed in US centers only. HCT using an HLA-identical sibling donor or unrelated donor or umbilical cord

blood. Age ≥ 18 years at HCT. First transplant only; second or later transplants will be excluded. The cohort will be restricted to centers that have performed ≥ 10 allogeneic

transplants for AML or ALL (from 2008 to 2010). Acute promyelocytic leukemia and therapy related/secondary AML will be excluded.

We will also look at how many patients from our study cohort were included in BMT CTN clinical trials. For the enrolled patients, we will examine whether the protocols specified a conditioning regimen / GVHD prophylaxis regimen, which could potentially impact transplant practices in a given center. Rationale for study population: Patient selection criteria have been chosen to have as homogenous a population as possible, so that “center” can be investigated as a potential predictor of transplant outcome.

We have restricted our study population to patients with AML and ALL since these are relatively standard indications for allogeneic HCT. Furthermore, focusing on a homogenous group of diseases would be preferable for addressing our study question (e.g. would minimize variation because of different timing of transplant, differences in conditioning regimens etc for other diseases).

We have limited this study to US centers; broader health care system factors (e.g. universal health coverage or restriction of HCT to selected centers) may impact center practices and subsequent patient outcomes in other countries.

Practices in adult and pediatric centers are very different. As noted above, since we primarily want to focus on center practices, we will restrict our analysis to adult patients in order to minimize impact of other factors (such as age) that can have a major impact on outcomes.

Also, we will include centers with an adequate number of transplants to describe practice variation among acute leukemia patients. Hence, we will restrict our patient population to centers that have performed ≥ 10 allogeneic HCT for AML or ALL during the study period.

4.0 OUTCOMES:

Overall survival – Analysis for overall survival will consider death from any cause. NRM – Non-relapse mortality will consider deaths from any cause other than relapse. Relapse – Recurrence of AML will be considered as relapse. Estimates for relapse will

consider the competing risk of death.

5.0 VARIABLES TO BE ANALYZED: TED level data will be used for this analysis. The following variables will be included in this analysis: Patient-related variables:

Age at transplant Race / ethnicity

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KPS score at transplant Co-existing disease (as described in the CIBMTR Annual Center Specific Analysis)

Center-related variables:

Center allogeneic transplant volume (total number of allogeneic transplants (any diagnosis) during the study period)

Disease-related variables:

Disease categories Time between diagnosis and transplant

Transplant-related variables:

Conditioning regimen intensity Cell source Donor source Donor-recipient gender match Donor-recipient CMV status Graft manipulation (e.g., T-cell depletion) Conditioning regimen GVHD prophylaxis regimen

6.0 STUDY DESIGN: (TO BE FINALIZED)

The analysis will consist of two parts: (1) description of center practice variation, and (2) impact of practice variation on outcomes of HCT. Objective #1: Description of center practice variation: We will describe practice variation across transplant centers using the metrics below. This analysis will describe how transplant centers in the US differ in the characteristics of patients transplanted for acute leukemia. As noted in the background section above, centers may control these factors to a certain level.

Age: Number of centers with median age at transplant < 40 vs. 40-60 vs. > 60 years Age: Number of centers where patients > 60 years constitute < 25% vs. 25-50%

vs.51-75% vs. > 75% of adult transplants for acute leukemia (based on data, may have to modify categories)

Disease status: Number of centers where patients with relapse/refractory disease status constitute < 25% vs. 25-50% vs.51-75% vs. > 75% of adult transplants for acute leukemia (based on data, may have to modify categories)

Donor source: Number of centers where HLA-identical sibling donor transplants constitute < 25% vs. 25-50% vs.51-75% vs. > 75% of adult transplants for acute leukemia (based on data, may have to modify categories)

Donor source: Number of centers where among unrelated/UCB donors, UCB constitutes < 25% vs. 25-50% vs.51-75% vs. > 75% of adult transplants for acute leukemia (based on data, may have to modify categories)

Donor source: Number of centers where among unrelated donors (no UCB), 8/8 HLA matched donors constitute < 90% vs. ≥ 90% of adult transplants for acute leukemia (based on data, may have to modify categories)

28


Graft type: Number of centers where among HLA-identical sibling donors, PB constitutes < 25% vs. 25-50% vs.51-75% vs. > 75% of adult transplants for acute leukemia (based on data, may have to modify categories)

Conditioning regimen: Number of centers where NMA/RIC regimens constitute < 25% vs. 25-50% vs.51-75% vs. > 75% of adult transplants for acute leukemia (based on data, may have to modify categories)

Conditioning regimen: Number of centers where among MA regimens, TBI constitutes < 25% vs. 25-50% vs.51-75% vs. > 75% of adult transplants for acute leukemia (based on data, may have to modify categories)

GVHD prophylaxis regimen: Number of centers where among MA regimens, MTX is included as part of GVHD prophylaxis in < 25% vs. 25-50% vs.51-75% vs. > 75% of adult transplants for acute leukemia (based on data, may have to modify categories)

Objective #2: Determine if center practice variation impacts outcomes The basic concept for this analysis would be to first investigate whether there is more variation in center outcomes than expected by chance. If yes, can center level factors explain the variability in outcomes. Based on our experience with other CIBMTR studies, we anticipate that there will be significant practice variation between centers. In this context, we will first estimate survival and other outcomes for each center and then compare whether these outcomes differ among various centers included in the cohort. Outcomes (overall survival, NRM, relapse) will be described at day 100 and 1 year after HCT. Probabilities of survival will be calculated using the Kaplan-Meier estimator. Cumulative incidence estimates will be obtained for NRM and relapse. Comparison of survival curves will be done using the log-rank test. Cox proportional hazards regression analysis will be used to evaluate the independent effect of practice variation on transplant outcomes. In addition to the main effect variables (center) the following variables will be considered: age at transplant, race / ethnicity, KPS score at transplant (≥ 90 vs. < 90), co-existing disease, center volume, disease status (AML CR1 vs. AML CR2 vs. ALL CR1 vs. ALL CR2), time between diagnosis and transplant (will check how this variable correlates with “disease status”), donor source (HLA-identical sibling vs. 8/8 matched unrelated vs. 5/6 or 6/6 matched UCB), cell source (BM vs. PB vs. UCB), donor-recipient gender match, donor-recipient CMV status, conditioning regimen (categories based on review of data) and GVHD prophylaxis regimen (categories based on review of data).

7.0 REFERENCES:

1. Lee SJ, Astigarraga CC, Eapen M, et al. Variation in supportive care practices in hematopoietic cell transplantation. Biol Blood Marrow Transplant. 2008;14:1231-1238.

2. Lee SJ, Joffe S, Artz AS, et al. Individual physician practice variation in hematopoietic cell transplantation. J Clin Oncol. 2008;26:2162-2170.

3. Loberiza FR, Jr., Zhang MJ, Lee SJ, et al. Association of transplant center and physician factors on mortality after hematopoietic stem cell transplantation in the United States. Blood. 2005;105:2979-2987.

4. Wennberg JE. Practice variation: implications for our health care system. Manag Care. 2004;13:3-7.

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5. Wennberg J, Gittelsohn. Small area variations in health care delivery. Science. 1973;182:1102-1108.

6. Grytten J, Sorensen R. Practice variation and physician-specific effects. J Health Econ. 2003;22:403-418.

7. Pasquini MC, Wang Z, Schneider L. Current use and outcome of hematopoietic stem cell transplantation: part I-CIBMTR Summary Slides, 2007. CIBMTR Newsletter [serial online]. 2007, 13(2):5-9. Available at: http://www.cibmtr.org/PUBLICATIONS/Newsletter/index.html Accessed 08/01/09.

8. Appelbaum FR. Allogeneic hematopoietic cell transplantation for acute myeloid leukemia when a matched related donor is not available. Hematology Am Soc Hematol Educ Program. 2008:412-417.

9. Gale RP, Horowitz MM, Rees JK, et al. Chemotherapy versus transplants for acute myelogenous leukemia in second remission. Leukemia. 1996;10:13-19.

10. Yanada M, Matsuo K, Emi N, Naoe T. Efficacy of allogeneic hematopoietic stem cell transplantation depends on cytogenetic risk for acute myeloid leukemia in first disease remission: a metaanalysis. Cancer. 2005;103:1652-1658.

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Table 1. Characteristics of AML and ALL patients receiving an allogeneic transplant at a US center during 2008-2010.

AML ALLCharacteristics N (%) N (%) Number of Patients 4311 1697 Number of Centers 118 125Median number of allo transplants during the study time period (range) 214 (17-1094) 212 (14-1094)Age of recipient at transplant Median (range) 52 (18-93) 40 (18-72) < 20 69 ( 2) 70 ( 4) 20-29 428 (10) 448 (26) 30-39 530 (12) 313 (18) 40-49 857 (20) 382 (23) 50-59 1259 (29) 336 (20) ≥ 60 1168 (27) 148 ( 9)Male 2302 (53) 976 (58)Race of recipient Hispanic 333 ( 8) 366 (22) Non-Hisp Caucasian 3565 (83) 1151 (68) Af-Am 188 ( 4) 87 ( 5) Asian / P.I. 163 ( 4) 62 ( 4) Other 62 ( 1) 31 ( 2)Karnofsky score pre-transplant ≥ 90 2717 (63) 1093 (64) < 90 1416 (33) 559 (33) Missing 178 ( 4) 45 ( 3)Sorror comorbidity score < 3 3063 (71) 1251 (74) ≥ 3 1176 (27) 407 (24) Missing 72 ( 2) 39 ( 2)Disease status at tx CR1 2333 (54) 1006 (59) CR2 851 (20) 393 (23) > CR3 76 ( 2) 64 ( 4) Relapse 492 (11) 167 (10) PIF 505 (12) 66 ( 4) Never treated 31 ( 1) 0 Missing 23 ( 1) 1 (<1)Time from dx to tx, months, median (range) 6 (0-312) 7 (1-418)Graft type BM 491 (11) 251 (15) PB 3415 (79) 1269 (75) CB 405 ( 9) 177 (10)

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Table 1. Continued. AML ALLCharacteristics N (%) N (%)HLA match HLA-identical sibling 1661 (39) 735 (43) Well-matched unrelated 1681 (39) 561 (33) Partially matched unrelated 464 (11) 188 (11) Mismatched unrelated 56 ( 1) 24 ( 1) Cord blood 405 ( 9) 177 (10) Missing HLA data 44 ( 1) 12 ( 1)Conditioning regimen RIC/NST 1250 (29) 230 (14) Myeloablative 3008 (70) 1442 (85) Missing 53 ( 1) 25 ( 1)Did pt get TBI for conditioning? No 2793 (65) 466 (27) Yes 1518 (35) 1231 (73)Donor / Recipient sex match Donor M / Recipient M 1397 (32) 592 (35) Donor M / Recipient F 1088 (25) 395 (23) Donor F / Recipient M 841 (20) 361 (21) Donor F / Recipient F 848 (20) 299 (18) Missing 137 ( 3) 50 ( 3)Donor / Recipient CMV match D- / R- 950 (22) 405 (24) D- / R+ 1368 (32) 456 (27) D+ / R- 438 (10) 186 (11) D+ / R+ 1380 (32) 596 (35) Missing 175 ( 4) 54 ( 3)Graft Manipulation No manipulation 4142 (96) 1648 (97) T-cell deplete 62 ( 1) 17 ( 1) Other graft manipulation 105 ( 2) 32 ( 2) Missing 2 (<1) 0GVHD Prophylaxis Not MTX containing 1843 (43) 631 (37) MTX containing 2466 (57) 1066 (63) Missing 2 (<1) 0Median follow-up of survivors, months 13 (<1 - 39) 13 (2 - 39)

Selection criteria N excluded N First allogeneic transplants only 319,697 Allos only 151,015 168,682 AML or ALL 94,299 74,383 2008-2010 62,574 11,809 US centers 3799 8010 HLA-sib, URD or CB 459 7551 Age ≥ 18 1367 6184 Restrict to centers with ≥ 10 transplants for AML, ALL in 2008-10 * 176 6008

* If we restrict to ≥ 5 transplants for AML, ALL in 2008-10, then N=6063

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Center characteristics (163 total centers): Age at transplant

Median age of patients at transplant centers Number of centers (%)

< 40 55 (34) 40-60 106 (65) > 60 2 ( 1)Percentage of patients at a transplant center that were > 60 years old at time of transplant 0 55 (34) 1-25% 80 (49) 25-50% 26 (16) 50-75% 1 ( 1) > 75% 1 ( 1) Disease status at transplant

Number of centers (%)





% of patients at a center transplanted in each disease status CR1 CR2 CR3 Relapse PIF

0 8 ( 5) 17 (10) 53 (33) 27 (17) 36 (22) 1-25% 6 ( 4) 68 (42) 109 (67) 126 (77) 125 (77) 25-50% 79 (48) 69 (42) 1 ( 1) 10 ( 6) 1 ( 1) 50-75% 63 (39) 4 ( 2) > 75% 7 ( 4) 5 ( 3) 1 ( 1) Donor source HLA-identical sibling transplants % of a center’s total transplants that received a transplant from an HLA-identical sibling


0 5 ( 3) 1-25% 30 (18) 25-50% 104 (64) 50-75% 13 ( 8) > 75% 11 ( 7)

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Cord blood transplants: 14 centers did only HLA-sib or other related transplants; therefore the total center count for URD is 149 Of unrelated donors, what % of a center’s transplants are CB transplants?


0 30 (20) 1-25% 48 (32) 25-50% 44 (30) 50-75% 14 ( 9) > 75% 13 ( 9)

Unrelated Bone Marrow and PBSC: 18 centers did only HLA-sib, other relative or CB only transplants; therefore the total center count for BM/PBSC transplants is 145. Of unrelated BM/PBSC, what % of a center’s transplants are 8/8 matched URD transplants?


0 7 ( 5) 1-90% 114 (79) ≥ 90% 24 (17)

Graft type HLA-identical sibling PBSC grafts. 5 centers did not do any HLA-identical sibling transplants; therefore the total center count for HLA-sib PBSC grafts is 158. Of HLA-identical sibling transplants, what % of a center’s transplants are PBSC grafts?


0 21 (13) 1-25% 12 ( 8) 25-50% 6 ( 4) 50-75% 17 (11) > 75% 102 (65)

Conditioning regimen RIC/NST regimens What % of a center’s transplants are RIC/NST regimens?


0 30 (18) 1-25% 65 (40) 25-50% 47 (29) 50-75% 12 ( 7) > 75% 9 ( 6)

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TBI use: 8 transplant centers did not do myeloablative conditioning; therefore the total center count here is 155. What % of a center’s patients that received myeloablative conditioning got TBI?


0 7 ( 5) 1-25% 20 (13) 25-50% 43 (28) 50-75% 56 (36) > 75% 29 (19)

GVHD Prophylaxis MTX use: 8 transplant centers did not do myeloablative conditioning; therefore the total center count here is 155. What % of a center’s patients that received myeloablative conditioning got MTX for GVHD prophylaxis?


0 6 ( 4) 1-25% 22 (14) 25-50% 28 (18) 50-75% 34 (22) > 75% 65 (42)

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CIBMTR HS11-01 GENERALIZABILITY OF BMT CTN 0201 RESULTS: PROGNOSTIC AND OUTCOME

DIFFERENCES BETWEEN PARTICIPANTS AND NONPARTICIPANTS

DRAFT PROTOCOL Study Chairs: Nandita Khera MD

Clinical Research Division Fred Hutchinson Cancer Research Center Seattle, WA 98109 Telephone: 206-667-5366 Fax: 206-667-1034 E-mail: [email protected]

Stephanie Lee, MD, MPH

Fred Hutchinson Cancer Research Center 1100 Fairview Avenue North, D5-290 PO Box 19024 Seattle, WA 98109

Telephone: 206-667-5160 Fax: 206-667-1034 E-mail: [email protected]

Study Statistician: Anna Hassebroek, MPH CIBMTR 3001 Broadway Street NE, Suite 110 Minneapolis, MN 55413 Telephone: 612-884-8611 Fax: 612-884-8661 E-mail: [email protected] Scientific Director: Navneet Majhail, MD, MS NMDP/CIBMTR 3001 Broadway Street NE, Suite 100 Minneapolis, MN 55413 Telephone: 612-884-8676 Fax: 612-884-8549 E-mail: [email protected]

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Working Committee Chairs: Susan Parsons, MD, MRP Tufts Medical Center 800 Washington St, #63 Boston, MA 02111 Telephone: 617-636-1450 Fax: 617-636-6280 E-mail: [email protected] Steve Joffe, MD, MPH Dana Farber Cancer Institute 44 Binney St. Boston, MA 02115 Telephone: 617-632-5295 Fax: 617-632-2270


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1.0 OBJECTIVES

This study will evaluate the generalizability of BMT CTN 0201 results utilizing data collected in the Stem Cell Therapeutics Outcomes Database (SCTOD). The study objectives are: 1.1 To examine the differences in characteristics of participants in BMT CTN protocol 0201

with the entire cohort of patients receiving unrelated donor HCTs at participating centers during the study time-period, including particular subsets of interest.

1.2 To evaluate any observed differences in clinical outcomes in the groups.

2.0 SCIENTIFIC JUSTIFICATION

Outcomes between trial participants and non-trial participants. Randomized clinical trials are considered to be the gold standard in research and are the most solid evidence to prompt changes in clinical care because of heightened internal validity. However, their applicability to a larger population may be limited because the patients entered into a trial may or may not be representative of the entire patient population. Participants in trials usually have prognostically favorable baseline characteristics because of patient or physician selection bias. Several studies have compared outcomes between cancer patients enrolled and not enrolled in clinical trials. The results are conflicting with some studies showing improved outcomes in the trial patients as compared to non-trial patients1-3 and others including two large reviews showing no trial effect4-7. Peppercorn et al. found that most studies comparing outcomes failed to control for potential confounding factors between trial participants and non-participants and found insufficient evidence to conclude that there is a trial effect on outcomes5. This controversy underscores the need to understand the generalizability of trial results to the entire population of patients to whom conclusions will be applied. By comparing the distribution of baseline factors in the trial and non-trial groups we can better understand the differences in clinical and biological characteristics between the study population and patients treated in a similar fashion outside the trial. It is also important to know the proportion of patients who were eligible for the study, and the proportion of eligible patients who eventually participated in the trial.

Significance of the current study

BMT CTN 0201 is a phase III randomized, multicenter study comparing G-CSF mobilized peripheral blood stem cells (PBSC) with marrow transplantation from HLA compatible unrelated donors. As a large randomized, multi-center study addressing an important question, it has the ‘practice changing potential’ in the field of hematopoietic cell transplantation. It is important to assess the distribution of prognostically important factors between patients treated on and off the study protocol in the same time period, and to compare their outcomes to understand the generalizability of trial results to the entire population of patients.

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3.0 STUDY POPULATION Two main cohorts of patients will be considered as illustrated in the figure: patients treated on BMT CTN protocol 0201 (Group A) and patients who underwent URD transplants during the study time period at each center who were not enrolled on 0201. The latter group will be divided into two subgroups: patients who appear eligible for 0201 by virtue of their clinical characteristics (primarily disease, conditioning regimen intensity, age) as reported to CIBMTR (group B1 + B2 = Group B) and patients who are clearly not eligible for 0201 based on reported characteristics (group C). Reasons why Group B did not participate in the trial will not be known except for the subset where the patient consented but the donor refused (B1). Other possible reasons that we will not be able to capture could be insurance denial, failure to present the trial to the patient, patient refusal, physician preferences, or enrollment on another clinical trial. Patients who do not consent for observational research through the CIBMTR database will not be included in the analysis. The final inclusion and exclusion criteria of the trial, relevant to the proposed study, are listed below: Inclusion Criteria:

Age 0 to 66 years Recipient-donor HLA match of 5/6 or 6/6 at HLA-A, B, DRB1 Transplant for the diagnosis of:

- Acute Myelogenous Leukemia in CR1, CR2, subsequent CRs, not in remission

- Acute Lymphoblastic Leukemia in CR1, CR2, subsequent CRs, not in remission

- Chronic Myelogenous Leukemia in chronic, accelerated or blast phase - Myelodysplastic syndromes-RA, RARS,RCMD,RCMD-RS, RAEB1 and 2,

MDS unclassified and MDS associated with isolated del(5q) - Myeloproliferative diseases - Patients with therapy-related AML or MDS whose prior malignancy has

been in remission for at least 12 months Exclusion Criteria:

Patients with prior allogeneic or autologous transplants using any hematopoietic stem cell source will be excluded from this trial except patients with secondary malignancies who have had a prior autologous transplant 12 or more months prior to enrollment

Diseases to be excluded are: lymphoma, other malignant disorders, and non-malignant disorders

4.0 STUDY OUTCOMES

Percentage of all URD transplants and all potentially eligible URD transplants that were

treated on the protocol Outcomes evaluated for CTN 0201:

Overall survival, acute graft-versus-host disease (GVHD), chronic GVHD, and relapse

Infections, time until off all immunosuppressive therapy, immune reconstitution and quality of life are additional endpoints in the BMT CTN 0201, but are not captured adequately in non-protocol participants. Thus, these endpoints will not be evaluated for the current study

39


Neutrophil and platelet engraftment, and graft failure are additional endpoints in the BMT CTN 0201 trial, but not of interest for the current study

4.1 Disease-free survival and treatment-related mortality will also be compared 5.0 VARIABLES TO BE ANALYSED

Main effect:

Participation in CTN 0201(Yes vs. No) Patient related:

Age: continuous, categorical by decade Gender: male vs. female Ethnicity: Hispanic vs. non-Hispanic Race: Caucasian vs. African-American vs. Asian/Pacific Islander vs. Other Karnofsky performance score at transplant: ≥ 90% vs. < 90% Co-morbid medical conditions: 0-1 vs. ≥ 2 conditions (Sorror HCT comorbidity

index added to the forms in 2007, therefore this information will not be available for transplants prior to 2007)

Disease related:

Disease type: to be determined Disease risk at transplant: low vs. intermediate vs. high

Transplant related:

Graft source: bone marrow vs. PBSC Donor age: categorical by decade Donor/recipient HLA match: 6/6 vs. 5/6 Donor-recipient sex-match: F-M vs. M-F vs. M-M vs. F-F Donor-recipient CMV match: -/- vs. -/+ vs. +/- vs. +/+ vs. unknown Conditioning regimen: Myeloablative vs. Reduced intensity Use of ATG for transplantation: no vs. yes GVHD prophylaxis: T-cell depletion vs. Csa + MTX vs. Csa ± others vs. FK506 +

MTX vs. FK506 ± others vs. Other vs. None Interval from diagnosis to transplant: continuous Year of transplant: continuous Transplant center

This variable list may be modified based on information available from the analysis of BMT CTN 0201 data. For example, any variables that are shown to be statistically significant predictors of outcome and which are available on non-trial participants will be added. Variables which are not significantly associated with any outcome may be eliminated, unless retained for descriptive purposes.

6.0 STUDY DESIGN The study time period at each center will be determined as the period of time between the first transplanted patient and the last transplanted patient on CTN 0201. This will give us a similar time frame for the two cohorts which may be different if we use the time period from study opening to closing or first enrolled patient to last enrolled patient as our study period because of a

40


potential lag of 1-2 months between the opening of the study or patient enrollment and actual transplant. Characteristics of Group A (CTN 0201 participants) will be compared with Group B + C (all non-participants) and with Group B (potentially eligible non-participants) using Wilcoxon rank sum, Chisquare, or Fisher’s exact test as appropriate. The goal of this descriptive analysis is to understand how representative CTN0201 participants are of the entire URD population at the participating centers and of the potentially eligible subset of URD patients. We will also compare Group A with the characteristics of potentially eligible patients who consented but whose donors declined (B1), since this is a subgroup of particular interest. Outcomes will be compared between Group A and Group B patients and with “donor declined” patients (Group B1) in univariate analyses. Multivariate analyses will evaluate the main effect of participation in BMT CTN 0201, adjusting for significant clinical characteristics. Protocol modifications affecting eligibility criteria that occurred during the conduct of CTN 0201 which are relevant to this generalizability study will be described but the analysis will not be adjusted for these considerations. By selecting the study period at each site based on when the first and last patients were transplanted on the study, we will control for some of these protocol amendments. If a center only enrolled one patient on 0201, then the time period ± 3 months from that enrollment will be selected. If a center enrolled at least one pediatric patient, then non-participating pediatric patients from the center will be included. If no pediatric patients were enrolled, then pediatric non-participants from that center will be excluded from the analysis.

7.0 REFERENCES

1. Braunholtz DA, Edwards SJ, Lilford RJ: Are randomized clinical trials good for us (in the short term)? Evidence for a "trial effect". J Clin Epidemiol 54:217-24, 2001

2. Davis S, Wright PW, Schulman SF, et al: Participants in prospective, randomized clinical trials for resected non-small cell lung cancer have improved survival compared with nonparticipants in such trials. Cancer 56:1710-8, 1985

3. Fossa SD, Skovlund E: Selection of patients may limit the generalizability of results from cancer trials. Acta Oncol 41:131-7, 2002

4. Mengis C, Aebi S, Tobler A, et al: Assessment of differences in patient populations selected for excluded from participation in clinical phase III acute myelogenous leukemia trials. J Clin Oncol 21:3933-9, 2003

5. Peppercorn JM, Weeks JC, Cook EF, et al: Comparison of outcomes in cancer patients treated within and outside clinical trials: conceptual framework and structured review. Lancet 363:263-70, 2004

6. Stiller CA, Benjamin S, Cartwright RA, et al: Patterns of care and survival for adolescents and young adults with acute leukaemia--a population-based study. Br J Cancer 79:658-65, 1999

7. Vist GE, Bryant D, Somerville L, et al: Outcomes of patients who participate in randomized controlled trials compared to similar patients receiving similar interventions who do not participate. Cochrane Database Syst Rev:MR000009, 2008

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CTN 0201Participants

“A”CTN 0201but no HCT Cords

CTN 0201 Pt consentedDnr refused

“B1”

CTN 0201Appears eligible*Not enrolled

“B2”

Not eligible“C”

A/A+B+C = % enrolled on 0201 of all URDsA/A+B= % enrolled of eligibleA vs. B1=similar except donor refused

*Based on disease, disease stage, HLA,BM or PB, age, donor from participating center

All URD transplants

Figure: Schema of distribution of patients

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Table 1. Characteristics of patients who received a BM or PBSC transplant between 2004 – 2009 according to their eligibility and enrollment in the BMTCTN 0201 clinical trial.

Enrolled Not Enrolled


Number of Patients 515 3401Number of Centers 46 44Age of recipient at transplant Median (range) 44 (<1-66) 48 (<1-78) ≤ 10 18 ( 3) 173 ( 5) < 20 34 ( 7) 234 ( 7) 20-29 83 (16) 375 (11) 30-39 78 (15) 434 (13) 40-49 102 (20) 632 (19) 50-59 133 (26) 897 (26) ≥ 60 66 (13) 656 (19) Missing 1 (<1) 0Male 290 (56) 1906 (56)Race/ethnicity of recipient Non-Hispanic White 455 (88) 2909 (86) African-American 21 ( 4) 120 ( 4) Asian/Pacific Islander 6 ( 1) 62 ( 2) Hispanic 19 ( 4) 250 ( 7) Other/unknown/missing 14 ( 3) 60 ( 2)Karnofsky score at transplant < 90 140 (27) 1092 (32) ≥ 90 320 (62) 1859 (55) Missing 55 (11) 450 (13)Disease AML 249 (48) 1795 (53) ALL 107 (21) 604 (18) Other leukemia 8 ( 2) 0 CML 59 (11) 304 ( 9) MDS 92 (18) 698 (21)

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Table 1. Continued.

Enrolled Not EnrolledCharacteristics N (%) N (%)

Disease status at transplant Early 236 (46) 1487 (44) Intermediate 125 (24) 811 (24) Advanced 111 (22) 876 (26) Missing 43 ( 8) 227 ( 7)Time from diagnosis to transplant, months, median (range) 8 (<1-1140) 8 (<1-606)HLA Match ≤ 4/6 0 9 (<1) 5/6 45 ( 9) 389 (11) 6/6 464 (90) 2929 (86) Missing 6 ( 1) 74 ( 2)Conditioning regimen Traditional ablative 368 (71) 2098 (62) RIC 134 (26) 1191 (35) Other 13 ( 3) 112 ( 3)GHVD Prophylaxis No GVHD prophylaxis 9 ( 2) 42 ( 1) Ex vivo T-cell depletion alone 0 7 (<1) Ex vivo T-cell depletion + post-tx IS 1 (<1) 21 ( 1) CD34 selection alone 0 1 (<1) CD34 selection + post-tx IS 0 6 (<1) FK506 + MMF +- others 47 ( 9) 422 (12) FK506 + MTX +- others (except MMF) 329 (64) 1821 (54) FK506 + others (except MTX, MMF) 26 ( 5) 242 ( 7) CSA + MMF +- others (except FK506) 5 ( 1) 271 ( 8) CSA + MTX +- others (except FK506, MMF) 86 (17) 442 (13) CSA + others (except FK506, MTX, MMF) 3 ( 1) 70 ( 2) Cortico + either MTX or MMF +-other 0 4 (<1) Other GVHD prophylaxis 9 ( 2) 52 ( 2)

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Table 1. Continued.

Enrolled Not EnrolledCharacteristics N (%) N (%)

ATG/Campath use ATG + Campath 0 1 (<1) ATG alone 133 (26) 944 (28) Campath alone 1 (<1) 129 ( 4) No ATG or Campath 376 (73) 2320 (68) Missing 5 ( 1) 7 (<1)Year of transplant 2004 30 ( 6) 661 (19) 2005 78 (15) 594 (17) 2006 97 (19) 599 (18) 2007 137 (27) 535 (16) 2008 111 (22) 535 (16) 2009 62 (12) 477 (14)Median follow-up of survivors, months 46 (<1 - 73) 48 (<1 - 89) Abbreviations: IS = Immune Suppresion *Not enrolled includes those that were eligible and were not eligible. Conditioning drug use needs to be cleaned before these two groups can be separated. **There were 551 patients/donors randomized to the 0201 trial. CIBMTR has data on 515 of these patients. 24 patients did not go to transplant; 9 got transplanted but we do not have forms on them; 3 got transplanted and CIBMTR is working to get the data retrieved.

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CIBMTR HS11-02

COMPARISON OF LENGTH OF STAY AMONG ALTERNATIVE GRAFT SOURCES: SINGLE

AND DOUBLE CORD BLOOD, MATCHED UNRELATED DONOR, OTHER RELATED DONOR

DRAFT PROTOCOL

Study Chair: Karen Ballen, MD Division of Hematology/Oncology

Massachusetts General Hospital Zero Emerson, Suite 118 Boston, MA 02114 Telephone: 617-724-1124 Fax: 617-724-1126 Email: [email protected]

Study Statistician: Anna Hassebroek, MPH CIBMTR 3001 Broadway St NE Minneapolis, MN 55413

Phone: 612-884-8611 Fax: 612-884-8661 E-mail: [email protected]

Scientific Director: Navneet Majhail, MD

CIBMTR National Marrow Donor Program 3001 Broadway St NE Minneapolis, MN 55413 Telephone 612-884-8676 Fax: 612-884-89549 Email: [email protected]

Working Committee Chairs: Steve Joffe, MD, MPH,

Dana Farber Cancer Institute and Children’s Hospital 44 Binney St Boston, MA 02115 Phone: 617-632-5295 Fax: 617- 632-2270 Email: [email protected]

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Working Committee Chairs: Susan Parsons,MD, MRP Tufts Medical Center 800 Washington St, #63 Boston, MA 02111 Phone 617-636-1450 Fax: 617-636-6280 Email: [email protected]

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1.0 OBJECTIVES:

1.0 To determine the length of stay in the first 100 days post transplant in recipients of single umbilical cord blood transplantation (UCB), double cord blood transplantation, matched unrelated donor bone marrow, matched unrelated peripheral blood stem cell transplants, and other related (non HLA identical sibling) transplants.

1.1 To determine risk factors for prolonged length of stay.

2.0 HYPOTHESIS: Length of stay is higher after UCB than after traditional stem cell sources, but double UCB reduces length of stay. Length of stay can be predicted by selected pre transplant variables.


Umbilical cord blood is an alternative stem cell source for patients without matched related or unrelated donors. Several studies have compared the results of unrelated donor transplants with cord blood transplants1-4. In general, engraftment is delayed in cord blood transplants, but the incidence of graft versus host disease is less. To overcome the issue of low cell dose in cord blood transplants, several investigators have used double cord blood transplant in adults, with either a myeloablative or reduced intensity preparative regimen5-8. Several studies, in both the pediatric and adult literature, have shown comparable survival among patients receiving unrelated cord blood or peripheral blood stem cell/marrow transplants9-11. Length of stay (LOS) or cost has not been compared in a large scale study among graft sources, however. Allogeneic stem cell transplantation is an expensive procedure, and health care resource allocation is now being analyzed closely. The median cost in Boston for an adult myeloablative allogeneic transplantation in 2004 was $102, 574 in the first 100 days, with a median hospital length of stay of 36 days.12 An unrelated donor transplant and advanced disease were associated with a higher cost. The same center reviewed costs with a reduced intensity regimen; median costs in the first 100 days were $42,149 for a reduced intensity transplant, with a median hospital length of stay of 21 days13. Recently, myeloablative transplants have moved to an outpatient setting, with one center reporting as study of 100 patients, with hospitalization only for complications; 18 patients required no in patient care and the median LOS was 15 days14. T cell depletion has also been associated with a 12% reduction in LOS15. In the pediatric setting, the use of outpatient total body radiation has been associated with a cost savings of $3250 per patient, and a 4 days shorter LOS16. A comparative study from Taiwan of 25 children receiving sibling transplants versus 29 children receiving unrelated cord blood transplant reveals that the LOS was 18 days shorter in the sibling group, but the readmission rate was similar17. The Minnesota group has compared costs in the first 100 days among umbilical cord blood myeloablative and reduced intensity recipients and matched related donor myeloablative and reduced intensity recipients18. The 100 day overall survival and transplant related mortality were similar among the different groups. The median cost per day survived (not including graft acquisition) was $1016 for myeloablative related donor, $2082 for myeloablative cord blood, $612 for nonmyeloablative related donor, and $1156 for nonmyeloablative cord blood. Higher costs were associated with the use of dialysis and mechanical ventilation. An earlier study from

48


the Netherlands compared costs of HLA identical sibling and unrelated donor transplants19. The average cost of a HLA identical sibling bone marrow transplant was 98,334 euros, HLA identical sibling peripheral blood stem cell transplant 98,977 euros, and for the matched unrelated donor transplant 151, 754 euros. These cost figures included donor identification and two years of follow-up. Double cord blood transplantation has been associated with a decreased risk of relapse and shorter time to engraftment5. Although the acquisition of a second cord blood unit is expensive, there may be cost efficiencies by decreasing LOS. In this study, we seek to compare LOS among different alternative graft sources, including single and double cord blood transplant, matched unrelated donor, and other related donor (haploidentical) transplant. Because costs vary from region to region, and are often difficult to ascertain, LOS in the first 100 days post transplant will be used as a surrogate marker of costs. This information will be of vital importance given the financial constraints on our health care system.

4.0 STUDY POPULATION:

The study population will consist of all patients with acute leukemia in remission receiving unrelated cord blood, matched unrelated donor with bone marrow or peripheral blood stem cell grafts, and haploidentical (mismatched related donor) transplant and were reported to the CIBMTR between 2004 and 2010. Single and double cord blood recipients, pediatric and adult patients, and patients treated with myeloablative, reduced intensity, and nonmyeloablative conditioning regimens are included. Only patients transplanted in US centers are included. The study will use outcome data collected on the existing data collection forms. No additional information would be required from the transplant centers.

5.0 STUDY OUTCOMES:

Number of hospital days (length of stay) in the first 100 days post transplant. 6.0 VARIABLES TO BE DESCRIBED:

Main effect (Graft Source): — Single cord blood unit — Double cord blood units — Matched (8/8 allele level) unrelated bone marrow transplant — Matched (8/8 allele level) unrelated peripheral blood stem cell transplant — Other related donor

7.0 VARIABLES TO BE ANALYZED:

Patient-related variables: — Age—continuous, categorical by decade — Gender-male vs. female — Karnofsky performance status prior to transplant: ≤ 80% vs. > 80% — Weight: continuous — Recipient CMV status: positive vs. negative vs. unknown

49


Disease-related variables: — Disease—AML vs. ALL — Disease stage—CR 1 or CR 2

Transplant-related variables:

— HLA match — Conditioning Regimen (ablative vs. nonablative/reduced intensity; TBI vs. non TBI) — GVHD prophylaxis (calcineurin inhibitor vs. other), use of ATG (horse and rabbit) — Cell dose—nucleated cell count/kg and CD34+ count/kg (Cord blood) – will be

added during data file preparation — Time from diagnosis to transplant— ≤ 12 vs. > 12 months — Year of transplant 2004-2007 vs. 2008-2010

8.0 STUDY DESIGN:

Per CIBMTR 9.0 REFERENCES:

1. Laughlin MJ, Eapen M, Rubinstein P, et al. Outcomes after transplantation of cord blood or bone marrow from unrelated donors in adults with leukemia. N Engl J Med 2004; 351: 2255-2275.

2. Rocha V, Labopin M, Sanz G, et al. Transplants of umbilical-cord blood or bone marrow from unrelated donors in adults with acute leukemia. N Engl J Med 2004; 351: 2276-2285.

3. Eapen M, Rocha V, Scaradavou A, et al. Effect of stem cell source on transplant outcomes in adults with acute leukemia: a comparison of unrelated bone marrow (BM), peripheral blood (PB), and cord blood (CB). Blood 2008; 112: 151a (abstract).

4. Takahashi S, Obi J, Tomoran A, et al. Comparative single institute analysis of cord blood transplantation from unrelated donors with bone marrow or peripheral blood stem-cell transplants from related donors in adult patients with hematologic malignancies after myeloablative conditioning regimen. Blood 2007; 109: 1322-1330.

5. Brunstein CG, Barker JN, Weisdorf DJ, et al. Umbilical cord blood transplantation after nonmyeloablative conditioning: impact on transplantation outcomes in 110 adults with hematologic disease. Blood 2007; 110: 3064-70.

6. Ballen KK, Spitzer TR, Yeap BY, et al. Double unrelated reduced-intensity umbilical cord blood transplantation in adults. Biol Blood Marrow Transplant 2007; 13: 82-89.

7. Barker JN, Weisdorf DJ, DeFor TE, et al. Transplantation of 2 partially HLA-matched umbilical cord blood units to enhance engraftment in adults with hematologic malignancy. Blood 2005; 105: 1343-47.

8. Majhail NS, Brunstein CG, Tomblyn M, et al. Reduced-intensity allogeneic transplant in patients older than 55 years: unrelated umbilical cord blood is safe and effective for patients without a matched related donor. Biol Blood Marrow Transplant 2008; 14: 282-89.

9. Eapen M, Rubinstein P, Zhang MJ et al. Outcomes of transplantation of unrelated donor umbilical cord blood and bone marrow in children with acute leukemia: a comparison study. Lancet 2007; 369: 1947-54.

10. Eapen M, Rocha V, Sanz G, et al. Effect of graft source on unrelated donor hematopoietic stem-cell transplantation in adults with acute leukemia: a retrospective analysis. Lancet 2010; 11: 653-660.

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11. Chen YB, Aldridge J, Kim H, et al. Reduced intensity conditioning (RIC) with double umbilical cord blood transplantation has similar outcomes compared to RIC transplantation from related or unrelated adult donors. Blood 2010; 116, 2367a (abstract).

12. Saito AM, Cutler C, Zahrieh D, et al. Costs of allogeneic hematopoietic cell transplantation with high-dose regimens. Biol Blood Marrow Transplant 2008; 142: 197-207.

13. Saito AM, Zahrieh D, Cutler C, et al. Lower costs associated with hematopoietic cell transplantation using reduced intensity vs high dose regimens for hematologic malignancy. Bone Marrow Transplant 2007; 40: 209-17.

14. Solomon SR, Matthews RH, Barreras AM, et al. Outpatient myeloablative allo-SCT: a comprehensive approach yields decreased hospital utilization and TRM. Bone Marrow Transplant 2010; 45: 468-75.

15. Lissovoy G, Hurd D, Carter S, et al. Economic analysis of unrelated allogeneic bone marrow transplantation: results from the randomized clinical trial of T cell depletion vs. unmanipulated grafts for the prevention of graft-versus-host disease. Bone Marrow Transplant 2005; 36: 539-46.

16. Farah RA, Aquino VM, Munoz LL, et al. Safety and cost effectiveness of outpatient total body irradiation in pediatric patients undergoing stem cell transplantation. Journ Pedi Heme/Onc 1998; 20: 319-21.

17. Jaing TH, Tsay PK, Yang CP, et al. Evaluation in readmission in children receiving allogeneic hematopoietic stem cell transplantation: an institutional experience. Transplantation Proceedings. 2008; 40: 3643-45.

18. Majhail NS, Mothkuri JM, Brunstein CG, Weisdorf DJ. Costs of hematopoietic cell transplantation: comparison of umbilical cord blood and matched related donor transplantation and the impact of post transplant complications. Biol Blood Marrow Transplant 2009; 15: 564-73.

19. Agthoven MV, Groot MT, Verdonck MT, et al. Cost analysis of HLA-identical sibling and voluntary unrelated allogeneic bone marrow and peripheral blood stem cell transplantation in adults with acute myelocytic leukemia or acute lymphoblastic leukemia. Bone Marrow Transplant 2002; 30: 243-51.

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Table 1a. Characteristics of pediatric patients (≤ 18) transplanted for acute leukemia in CR1 or CR2 between 2008-2010.

Double CB Single CB

Matched URD BM

Matched URD

PBSC Other

relative ≤ 7/8 BM ≤ 7/8 PBSC

Characteristics N (%) N (%) N (%) N (%) N (%) N (%) N (%)Number of Patients 269 70 106 23 22 35 21Number of Centers 57 34 43 17 13 25 14Age at transplant Median (range) 8 (<1-18) 5 (<1-17) 9 (<1-18) 10 (<1-18) 11 (1-18) 13 (<1-18) 14 (3-18) < 10 161 (60) 50 (71) 56 (53) 12 (52) 9 (41) 13 (37) 3 (14) 10-19 108 (40) 20 (29) 50 (47) 11 (48) 13 (59) 22 (63) 18 (86) Male 145 (54) 35 (50) 62 (58) 8 (35) 12 (55) 19 (54) 12 (57)Karnofsky status pre-tx ≤ 80 29 (11) 10 (14) 7 ( 7) 4 (17) 1 ( 5) 4 (11) 2 (10) 90-100 223 (83) 57 (81) 93 (88) 17 (74) 21 (95) 31 (89) 18 (86) Missing 17 ( 6) 3 ( 4) 6 ( 6) 2 ( 9) 0 0 1 ( 5)Disease AML 100 (37) 26 (37) 53 (50) 11 (48) 9 (41) 19 (54) 11 (52) ALL 132 (49) 37 (53) 27 (25) 6 (26) 12 (55) 9 (26) 8 (38) MDS 37 (14) 7 (10) 26 (25) 6 (26) 1 ( 5) 7 (20) 2 (10)Disease status at tx AML/ALL CR1 113 (42) 35 (50) 40 (38) 10 (43) 8 (36) 17 (49) 13 (62) AML/ALL CR2 120 (45) 28 (40) 40 (38) 7 (30) 13 (59) 11 (31) 6 (29) MDS 36 (13) 7 (10) 26 (25) 6 (26) 1 ( 5) 7 (20) 2 (10)Time from dx to tx, months Median (range) 8 (<1-152) 7 (1-65) 6 (1-107) 6 (2-88) 20 (3-115) 6 (<1-36) 8 (1-26) < 6 mos 116 (43) 33 (47) 53 (50) 12 (52) 8 (36) 17 (49) 10 (48) 6-11 mos 46 (17) 14 (20) 13 (12) 2 ( 9) 0 7 (20) 4 (19) 12-18 mos 33 (12) 4 ( 6) 19 (18) 3 (13) 3 (14) 4 (11) 5 (24) > 18 mos 74 (28) 19 (27) 21 (20) 6 (26) 11 (50) 6 (17) 2 (10) Missing 0 0 0 0 0 1 ( 3) 0

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Table 1a. Continued.

Double CB Single CB

Matched URD BM

Matched URD

PBSC Other


Characteristics N (%) N (%) N (%) N (%) N (%) N (%) N (%)Conditioning regimen Traditional ablative 225 (84) 59 (84) 80 (75) 18 (78) 13 (59) 32 (91) 16 (76) RIC 30 (11) 9 (13) 21 (20) 4 (17) 9 (41) 3 ( 9) 5 (24) Missing 14 ( 5) 2 ( 3) 5 ( 5) 1 ( 4) 0 0 0TBI use No 72 (27) 25 (36) 57 (54) 12 (52) 8 (36) 20 (57) 10 (48) Yes 194 (72) 43 (61) 49 (46) 11 (48) 14 (64) 15 (43) 11 (52) Missing 3 ( 1) 2 ( 3) 0 0 0 0 0GHVD Prophylaxis No GVHD prophylaxis 14 ( 5) 2 ( 3) 7 ( 7) 0 1 ( 5) 3 ( 9) 0 Ex vivo T-cell depletion alone 0 0 0 0 0 0 2 (10) Ex vivo T-cell depletion + post-tx IS 0 0 0 0 2 ( 9) 1 ( 3) 3 (14) CD34 selection alone 0 0 0 0 3 (14) 0 0 CD34 selection + post-tx IS 0 0 0 0 2 ( 9) 0 1 ( 5) FK506 + MMF +- others 27 (10) 8 (11) 9 ( 8) 1 ( 4) 4 (18) 4 (11) 2 (10) FK506 + MTX +- others (except MMF) 27 (10) 10 (14) 34 (32) 15 (65) 3 (14) 10 (29) 5 (24) FK506 + others (except MTX, MMF) 8 ( 3) 1 ( 1) 6 ( 6) 1 ( 4) 1 ( 5) 3 ( 9) 1 ( 5) CSA + MMF +- others (except FK506) 146 (54) 26 (37) 7 ( 7) 2 ( 9) 1 ( 5) 1 ( 3) 4 (19) CSA + MTX +- others (except FK506, MMF) 13 ( 5) 2 ( 3) 38 (36) 3 (13) 5 (23) 12 (34) 3 (14) CSA + others (except FK506, MTX, MMF) 28 (10) 21 (30) 3 ( 3) 1 ( 4) 0 1 ( 3) 0 Other GVHD prophylaxis 6 ( 2) 0 2 ( 2) 0 0 0 0ATG/Campath use ATG alone 92 (34) 34 (49) 44 (42) 9 (39) 4 (18) 15 (43) 10 (48) CAMPATH alone 4 ( 1) 0 9 ( 8) 2 ( 9) 4 (18) 3 ( 9) 1 ( 5) No ATG or CAMPATH 173 (64) 36 (51) 52 (49) 12 (52) 14 (64) 17 (49) 10 (48) Missing 0 0 1 ( 1) 0 0 0 0

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Table 1a. Continued.

Double CB Single CB Matched URD BM

Matched URD

PBSC Other


Characteristics N (%) N (%) N (%) N (%) N (%) N (%) N (%) Year of transplant 2008 84 (31) 29 (41) 40 (38) 8 (35) 16 (73) 15 (43) 12 (57) 2009 107 (40) 25 (36) 37 (35) 2 ( 9) 6 (27) 12 (34) 5 (24) 2010 78 (29) 16 (23) 29 (27) 13 (57) 0 8 (23) 4 (19) Total number of inpatient days in first 100 days post-HSCT Median (range) 48 (4-179) 46 (22-100) 40 (17-100) 36 (4-70) 38 (18-95) 43 (17-100) 49 (5-100) < 14 4 ( 1) 0 0 2 ( 9) 0 0 1 ( 5) 15-29 36 (13) 11 (16) 28 (26) 9 (39) 6 (27) 7 (20) 5 (24) 30-45 81 (30) 22 (31) 34 (32) 8 (35) 10 (45) 12 (34) 3 (14) > 45 145 (54) 36 (51) 43 (41) 4 (17) 6 (27) 16 (46) 12 (57) Missing 3 ( 1) 1 ( 1) 1 ( 1) 0 0 0 0 Median follow-up of survivors, months 23 (3 - 39) 24 (4 - 36) 24 (3 - 42) 14 (6 - 36) 35 (24 - 37) 25 (7 - 36) 23 (7 - 38)

* Median follow-up was calculated using the KM method; the range of follow-up was calculated from all alive patients

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Number of inpatient days in the first 100-days post-HSCT for pediatric patients by year of transplant. < 14 15-29 30-45 > 45 Missing

Year of transplant N % N % N % N % N % 2004 1 0.53 13 6.91 11 5.85 16 8.51 147 78.22005 0 . 6 3.14 12 6.28 7 3.66 166 86.92006 0 . 5 2.13 11 4.68 13 5.53 206 87.72007 2 0.9 20 8.97 40 17.9 49 22 112 50.22008 2 0.98 38 18.6 73 35.8 90 44.1 1 0.492009 0 . 37 19.1 51 26.3 103 53.1 3 1.552010 5 3.38 27 18.2 46 31.1 69 46.6 1 0.68

Number of inpatient days in the first 100-days post-HSCT for all pediatric patients by conditioning regimen.

<14 15-29 30-45 >45 Conditioning regimen N % N % N % N % N Median Min MaxTraditional ablative 4 0.91 79 17.95 143 32.5 214 48.64 440 44 4 121RIC 3 3.75 19 23.75 20 25 38 47.5 80 41.5 5 100Missing 0 4 19.05 7 33.33 10 47.62 21 45 16 179

Number of inpatient days in the first 100-days post-HSCT for pediatric patients that survived through 100 days by conditioning regimen.

<14 15-29 30-45 >45 Conditioning regimen N % N % N % N % N Median Min MaxTraditional ablative 2 0.52 72 18.9 132 34.65 175 45.93 381 43 4 121RIC 3 4.69 17 26.56 17 26.56 27 42.19 64 37.5 5 100Missing 0 4 21.05 6 31.58 9 47.37 19 45 16 179

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Number of inpatient days in the first 100-days post-HSCT for all pediatric patients by Karnofsky status pre-transplant.

<14 15-29 30-45 >45 Karnofsky status pre-transplant N % N % N % N % N Median Min Max≤ 80 1 1.75 5 8.77 16 28.07 35 61.4 57 52 9 10090-100 6 1.32 92 20.18 145 31.8 213 46.71 456 43.5 4 121Missing 0 5 17.86 9 32.14 14 50 28 45.5 16 179

Number of inpatient days in the first 100-days post-HSCT for pediatric patients that survived through 100 days by Karnofsky status pre-transplant.

<14 15-29 30-45 >45 Karnofsky status pre-transplant N % N % N % N % N Median Min Max≤ 80 1 2.04 5 10.2 14 28.57 29 59.18 49 52 9 10090-100 4 1.03 83 21.28 134 34.36 169 43.33 390 42 4 121Missing 0 5 20 7 28 13 52 25 46 16 179

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Table 1b. Characteristics of adult patients (> 18) transplanted for acute leukemia in CR1 or CR2 between 2008-2010.

Double CB Single CB

Matched URD BM

Matched URD

PBSC Other


Characteristics N (%) N (%) N (%) N (%) N (%) N (%) N (%) Number of Patients 396 26 207 1014 101 55 323 Number of Centers 65 11 57 93 33 35 75 Age at transplant Median (range) 49 (19-72) 49 (20-66) 49 (19-71) 53 (19-78) 53 (23-73) 45 (19-64) 49 (19-72) 10-19 8 ( 2) 0 2 ( 1) 8 ( 1) 0 3 ( 5) 3 ( 1) 20-29 74 (19) 7 (27) 34 (16) 97 (10) 12 (12) 15 (27) 38 (12) 30-39 56 (14) 3 (12) 28 (14) 114 (11) 11 (11) 4 ( 7) 46 (14) 40-49 70 (18) 4 (15) 48 (23) 221 (22) 19 (19) 13 (24) 78 (24) 50-59 101 (26) 5 (19) 70 (34) 329 (32) 22 (22) 14 (25) 96 (30) 60-69 81 (20) 7 (27) 23 (11) 222 (22) 32 (32) 6 (11) 60 (19) ≥ 70 6 ( 2) 0 2 ( 1) 23 ( 2) 5 ( 5) 0 2 ( 1) Male 196 (49) 8 (31) 110 (53) 554 (55) 59 (58) 23 (42) 182 (56) Karnofsky status pre-transplant ≤ 80 103 (26) 4 (15) 47 (23) 345 (34) 22 (22) 15 (27) 109 (34) 90-100 266 (67) 22 (85) 144 (70) 589 (58) 70 (69) 37 (67) 186 (58) Missing 27 ( 7) 0 16 ( 8) 80 ( 8) 9 ( 9) 3 ( 5) 28 ( 9) Disease AML 234 (59) 16 (62) 121 (58) 567 (56) 58 (57) 34 (62) 176 (54) ALL 91 (23) 6 (23) 28 (14) 102 (10) 24 (24) 11 (20) 37 (11) MDS 71 (18) 4 (15) 58 (28) 345 (34) 19 (19) 10 (18) 110 (34) Disease status at transplant AML/ALL CR1 201 (51) 17 (65) 106 (51) 505 (50) 53 (52) 28 (51) 145 (45) AML/ALL CR2 124 (31) 5 (19) 43 (21) 167 (16) 29 (29) 17 (31) 68 (21) MDS 71 (18) 4 (15) 58 (28) 342 (34) 19 (19) 10 (18) 110 (34) Time from diagnosis to transplant, months Median (range) 8 (2-312) 9 (2-55) 6 (<1-167) 7 (<1-357) 7 (2-93) 8 (3-90) 7 (<1-342) < 6 mos 145 (37) 6 (23) 96 (46) 449 (44) 41 (41) 15 (27) 111 (34) 6-11 mos 101 (26) 11 (42) 61 (29) 268 (26) 30 (30) 25 (45) 112 (35) 12-18 mos 62 (16) 5 (19) 18 ( 9) 92 ( 9) 10 (10) 7 (13) 38 (12) > 18 mos 88 (22) 4 (15) 32 (15) 203 (20) 20 (20) 8 (15) 60 (19) Missing 0 0 0 2 (<1) 0 0 2 ( 1)

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Table 1b. Continued.

Double CB Single CB

Matched URD BM

Matched URD

PBSC Other

relative ≤7/8 BM ≤7/8

PBSC Characteristics N (%) N (%) N (%) N (%) N (%) N (%) N (%) Conditioning regimen Traditional ablative 168 (42) 19 (73) 135 (65) 559 (55) 22 (22) 35 (64) 172 (53) RIC 216 (55) 7 (27) 66 (32) 403 (40) 72 (71) 20 (36) 133 (41) Missing 12 ( 3) 0 6 ( 3) 52 ( 5) 7 ( 7) 0 18 ( 6) TBI use No 81 (20) 9 (35) 135 (65) 729 (72) 37 (37) 25 (45) 227 (70) Yes 314 (79) 17 (65) 72 (35) 281 (28) 60 (59) 30 (55) 95 (29) Missing 1 (<1) 0 0 4 (<1) 4 ( 4) 0 1 (<1) GHVD Prophylaxis No GVHD prophylaxis 14 ( 4) 1 ( 4) 18 ( 9) 27 ( 3) 11 (11) 5 ( 9) 4 ( 1) Ex vivo T-cell depletion alone 0 0 0 1 (<1) 7 ( 7) 0 1 (<1) Ex vivo T-cell depletion + post-tx IS 0 0 0 0 10 (10) 0 2 ( 1) CD34 selection alone 1 (<1) 0 0 0 1 ( 1) 0 0 CD34 selection + post-tx IS 0 1 ( 4) 0 1 (<1) 1 ( 1) 0 4 ( 1) Cyclophosphamide + others 0 0 0 0 6 ( 6) 0 0 FK506 + MMF +- others 136 (34) 1 ( 4) 19 ( 9) 181 (18) 36 (36) 13 (24) 55 (17) FK506 + MTX +- others (except MMF) 11 ( 3) 1 ( 4) 131 (63) 600 (59) 12 (12) 24 (44) 181 (56) FK506 + others (except MTX, MMF) 27 ( 7) 4 (15) 14 ( 7) 87 ( 9) 8 ( 8) 5 ( 9) 37 (11) CSA + MMF +- others (except FK506) 200 (51) 16 (62) 3 ( 1) 57 ( 6) 3 ( 3) 0 19 ( 6) CSA + MTX +- others (except FK506, MMF) 2 ( 1) 1 ( 4) 12 ( 6) 37 ( 4) 2 ( 2) 5 ( 9) 13 ( 4) CSA + others (except FK506, MTX, MMF) 1 (<1) 1 ( 4) 3 ( 1) 9 ( 1) 2 ( 2) 1 ( 2) 2 ( 1) Cortico + either MTX OR MMF +-Other 0 0 0 0 0 1 ( 2) 0 Other GVHD prophylaxis 4 ( 1) 0 7 ( 3) 14 ( 1) 2 ( 2) 1 ( 2) 5 ( 2) ATG/Campath use ATG alone 112 (28) 8 (31) 67 (32) 365 (36) 10 (10) 25 (45) 152 (47) CAMPATH alone 1 (<1) 0 2 ( 1) 26 ( 3) 4 ( 4) 2 ( 4) 4 ( 1) No ATG or CAMPATH 283 (71) 18 (69) 138 (67) 623 (61) 87 (86) 28 (51) 164 (51) Missing 0 0 0 0 0 0 3 ( 1)

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Table 1b. Continued.

Double CB Single

CB Matched URD BM

Matched URD PBSC

Other relative ≤7/8 BM ≤7/8 PBSC

Characteristics N (%) N (%) N (%) N (%) N (%) N (%) N (%) Year of transplant 2008 113 (29) 18 (69) 77 (37) 369 (36) 67 (66) 24 (44) 134 (41) 2009 150 (38) 4 (15) 76 (37) 382 (38) 27 (27) 17 (31) 124 (38) 2010 133 (34) 4 (15) 54 (26) 263 (26) 7 ( 7) 14 (25) 65 (20) Total number of inpatient days in first 100 days post-HSCT Median (range) 38 (<1-117) 32 (15-85) 29 (<1-100) 24 (<1-106) 22 (<1-100) 36 (13-95) 27 (<1-137) <14 29 ( 7) 0 13 ( 6) 168 (17) 31 (31) 1 ( 2) 37 (11) 15-29 92 (23) 9 (35) 91 (44) 508 (50) 39 (39) 18 (33) 138 (43) 30-45 127 (32) 13 (50) 67 (32) 216 (21) 13 (13) 14 (25) 72 (22) >45 148 (37) 4 (15) 35 (17) 115 (11) 16 (16) 20 (36) 74 (23) Missing 0 0 1 (<1) 7 ( 1) 2 ( 2) 2 ( 4) 2 ( 1) Median follow-up of survivors, months 20 (3 - 43) 34 (6 - 39) 24 (5 - 40) 24 (2 - 44) 24 (6 - 38) 25 (6 - 43) 24 (4 - 41)

* Median follow-up was calculated using the KM method; the range of follow-up was calculated from all alive patients

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Number of inpatient days in the first 100-days post-HSCT for adult patients by year.

<14 15-29 30-45 >45 Missing Year of transplant N % N % N % N % N % 2004 3 0.68 7 1.59 3 0.68 4 0.91 423 96.12005 0 6 1 3 0.5 3 0.5 589 982006 3 0.4 19 2.55 8 1.07 4 0.54 711 95.42007 46 5.77 160 20.1 89 11.2 77 9.66 425 53.32008 131 16.3 327 40.8 188 23.4 149 18.6 7 0.872009 94 12.1 337 43.2 196 25.1 149 19.1 4 0.512010 54 10 231 42.8 138 25.6 114 21.1 3 0.56

Number of inpatient days in the first 100-days post-HSCT for all adult patients by conditioning regimen.

<14 15-29 30-45 >45 Conditioning regimen N % N % N % N % N Median Min MaxTraditional ablative 77 7.03 503 45.94 293 26.76 222 20.27 1095 28 1 137RIC 155 17.32 353 39.44 207 23.13 180 20.11 895 26 1 117Missing 12 14.46 39 46.99 22 26.51 10 12.05 83 25 1 80

Number of inpatient days in the first 100-days post-HSCT for adult patients that survived through 100 days by conditioning regimen.

<14 15-29 30-45 >45 Conditioning regimen N % N % N % N % N Median Min MaxTraditional ablative 68 7.42 461 50.33 225 24.56 162 17.69 916 27 1 137RIC 139 18.46 328 43.56 163 21.65 123 16.33 753 25 1 117Missing 12 16.44 35 47.95 20 27.4 6 8.22 73 25 1 80

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Number of inpatient days in the first 100-days post-HSCT for all adult patients by Karnofsky status pre-transplant.

<14 15-29 30-45 >45 Karnofsky status pre-transplant N % N % N % N % N Median Min Max≤ 80 88 13.86 249 39.21 174 27.4 124 19.53 635 28 1 10690-100 138 10.78 579 45.23 307 23.98 256 20 1280 27 1 137Missing 18 11.39 67 42.41 41 25.95 32 20.25 158 28 2 100

Number of inpatient days in the first 100-days post-HSCT for adult patients that survived through 100 days by Karnofsky status pre-transplant.

<14 15-29 30-45 >45 Karnofsky status pre-transplant N % N % N % N % N Median Min Max≤ 80 78 15 224 43.08 130 25 88 16.92 520 26 1 10090-100 124 11.37 538 49.31 246 22.55 183 16.77 1091 26 1 137Missing 17 12.98 62 47.33 32 24.43 20 15.27 131 26 2 100

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Selection criteria:

N excluded N First allogeneic transplants only 82,652 AML, ALL or MDS 38,626 44,026 2008 - 2010 38,056 5970 Pts with complete report forms 512 5458 Pts who consented 212 5246 US centers only 519 4727 Delete HLA matched siblings 1250 3477 Delete other/missing graft type and HLA match (will review during data file preparation)

155 3322

Keep CR1 or CR2 only (AML/ALL) 654 2668

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CIBMTR HS10-01

OUTCOMES OF HEMATOPOIETIC CELL TRANSPLANTATION FOR ADOLESCENTS AND

YOUNG ADULTS (AYA) WITH ALL

DRAFT PROTOCOL

Study Co-chairs: William Wood, MD, MPH, University of North Carolina 122 Shadow Ridge Place Chapel Hill, NC, 27516 Telephone: 919-843-6517 Fax: 919-966-6735 E-mail: [email protected] Stephanie Lee, MD, MPH Fred Hutchinson Cancer Research Center 1100 Fairview Avenue North, D5-290 PO Box 19024 Seattle, WA 98109 Telephone: 206-667-5160 Fax: 206-667-1034 E-mail: [email protected] Study Statistician: Anna Hassebroek, MPH CIBMTR 3001 Broadway Street NE, Suite 110 Minneapolis, MN 55413 Telephone: 612-884-8611 Fax: 612-884-8661 E-mail: [email protected] Scientific Director: Navneet Majhail, MD, MS University of Minnesota MMC 480, 420 Delaware Street SE Minneapolis, MN 55455 Telephone: 612-624-6982 Fax: 612-625-6919 E-mail: [email protected]

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Working Committee Susan Parsons, MD, MRP Co-Chairs: Tufts Medical Center 800 Washington St, #63 Boston, MA 02111 Telephone: 617-636-1450 Fax: 617-636-6280 E-mail: [email protected] Steve Joffe, MD, MPH Dana Farber Cancer Institute 44 Binney St. Boston, MA 02115 Telephone: 617-632-5295 Fax: 617-632-2270 E-mail: [email protected]

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1.0 OBJECTIVES:

1.1 To determine whether the rate of improvement in transplant outcomes (5-yr OS, PFS, TRM) for AYA recipients (15-39 years) with ALL from 1990 to 2007 is less than in younger (0-14 years) or older (40+ years) recipients.

1.2 To investigate whether center effects or socioeconomic factors are associated with 5-yr

OS, PFS and TRM among AYA ALL recipients transplanted between 2002 and 2007. If sample size permits, age subcategorizations will include ages 15-21, 22-30, and 31-40.


Adolescent and young adult (AYA) patients with cancer have been designated as a high risk group by the National Cancer Institute, and have experienced smaller improvements in conditional survival over time than younger or older patient populations with cancer.1 Some of the reasons for this disparity have been attributed to differences in receipt of supportive care and psychosocial characteristics of this population.2 The hypotheses of this study are twofold. The first relates to trends in outcomes over time. We hypothesize that AYAs with ALL will have experienced smaller improvements in transplant outcomes over time (1990-2007) relative to younger and older cohorts. If this turns out to be true, this observation will in turn be hypothesis-generating, as the reasons for this discrepancy will not be fully evaluable using this data set. The second set of hypotheses relates to a recent AYA HCT cohort (2002-2007). In this cohort, we hypothesize that center effects and socioeconomic characteristics will be associated with transplant outcomes. For example, in this recent cohort we hypothesize that pediatric transplant centers and centers with higher AYA and non-AYA transplant volume will be associated with superior HCT outcomes for AYAs. We also hypothesize that lower household income and longer distance from the transplant center will be associated with worse outcomes among AYAs. In this second set of analyses, we will not compare the AYA cohort to younger or older recipients. Issues unique to AYAs have been previously observed to affect outcomes following standard chemotherapy treatment for ALL. Multiple prior studies have demonstrated disparate outcomes for adolescents treated on pediatric vs adult protocols for ALL.3 This observation has stimulated intense debate about what the most important contributors might be to this phenomenon. Significant attention has appropriately focused on the type and intensity of anti-leukemic treatment in the different protocols. However, some have also speculated that compliance and supportive care may account for some of the observed survival disparities. In children, poor adherence to oral mercaptopurine therapy during maintenance therapy for ALL has been associated with relapse and inferior survival.4 There is evidence that different sociodemographic groups have different survival rates in pediatric ALL, and the observation that survival in these groups appears to be associated with attendance at clinic visits suggests that medication adherence may contribute to this finding as well.5 Additionally, a large body of literature supports the hypothesis that complex developmental factors unique to the adolescent age group may also be associated with nonadherence,6,7 whether to medications or other elements of treatment. The direct involvement of parents in the medical care of adolescents may help to decrease this effect. It may be in part for these kinds of reasons that Stock et. al. made the surprising observation that although 16-17 year old patients treated on CALGB protocols had similar event free survival rates to 16-20 year old patients treated on COG protocols, 18-20 year old patients treated on

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CALGB protocols had significantly inferior EFS rates.8 One possible explanation that Stock offered was “emancipated adolescence;” 18-20 year olds treated on CALGB protocols might have been more likely to be living independently and removed from family members who would have otherwise improved protocol compliance. In a follow-up letter to Blood, Drs. Kantarjian and O’Brien suggested that perhaps the CALGB 18-20 year olds were also relatively underinsured, or “emancipated from (their parents’) insurance” relative to their COG counterparts, and this might have also contributed to reduced protocol adherence.9 Another possible contributor might be different developmental approaches and expectations in adult vs. pediatric clinics for protocol and supportive care compliance among adolescents and young adults. In thinking further about the entire 15-39 year old age group, we can envision additional psychosocial barriers to care that are commonly described in the AYA population as patients grow older. These include: financial and transportation difficulties compounded by living independently, starting at the bottom rung of the job ladder and possibly caring for young children; possible lack of a committed caregiver, if away from parents and not yet in a long-term relationship; ongoing issues with underinsurance; interpersonal, emotional, and existential issues; and low baseline self-efficacy, which typically develops with growth as a young adult. Allogeneic HCT survivorship entails considerable demands in self-care and compliance with post-transplant treatment recommendations. The consequences of an inability to appropriately adhere to a complex medication regimen that includes immunosuppressives, or to obtain early and prompt medical care for developing complications, can be life-threatening and might be a contributor to treatment-related mortality. Recently published studies about the use of HCT in ALL, particularly in first remission, have highlighted the centrality of TRM estimates to the benefit of the procedure. The MRC/ECOG study published in Blood in February 2008 analyzed 1913 patients with ALL in CR1 on a donor (matched sibling) vs. no donor basis.10 The authors found that the donor group had a 5 year improved overall survival, but the survival difference compared to the no-donor group was only significant for standard-risk and not high-risk patients. This was because of the high rates of TRM in the high-risk group; at 2 years, the TRM for high-risk patients was 36%, versus 20% for standard risk patients. Of interest, the OS for 234 Philadelphia chromosome-negative patients less than 20 years old in this study was only 43%, approximately 25% lower than absolute survival rates in pediatric chemotherapy-only trials for ALL in North America and Europe during the same time frame.11 The HOVON paper in Blood in February 2009 looked at 287 patients with ALL in CR1, also compared on a donor (96) vs no-donor (161) basis.12 The authors concluded that DFS after 5 years was significantly better in the donor group, but after risk-group analysis, the improvements in outcome were greater in standard-risk patients than in high-risk patients. NRM was approximately 16% at 5 years in the entire cohort, and was not significantly different between the standard-risk and high-risk groups, in contrast to the MRC/ECOG study. In their discussion, the investigators concluded that the greatest benefit of HCT in ALL patients in 1st CR was likely to be realized in those with a relapse risk exceeding 50% and an NRM risk of less than 20% to 25%, and noted that “it is imperative that the risk of NRM should be taken into account in decision making.” In a retrospective study from the University of Minnesota published in the Journal of Clinical Oncology in August 2009, the authors looked at 623 consecutive patients who received myeloablative HCT for ALL.13 Several patients were transplanted in CR2. Among a more recent cohort of patients in this study transplanted between 1990 and 2005 from related donors, the 2 year TRM was 26%. TRM was noted to be progressively and significantly lower since 1995.

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Limitations. The CIBMTR database does not have the ability to account for factors such as type of pre-HCT chemotherapy received, compliance with pre-HCT chemotherapy, or even receipt of or compliance with post-HCT supportive care. However, because these factors are thought to be particularly important in the AYA population, this study may provide rationale for further investigation of these issues in the HCT setting if HCT outcomes over time are found to lag in the AYA population in comparison with younger and older cohorts. We acknowledge that pre-HCT patient selection may also account for disparities in outcomes over time, so this issue would also require further study as a competing explanation if disparities are seen in this analysis. However, our investigation of center effects (including adult vs pediatric center) and socioeconomic factors (including estimated household income) in a recent AYA HCT cohort may provide indirect evidence that these kinds of issues are relevant to transplant outcomes in these patients.


Reported transplants between the years 1990-2007 Allogeneic transplants only Transplanted in US Disease: ALL (delete NK cell leuk) Disease status: CR1 or CR2 Graft type: PBSC or BM (UCB grafts are excluded) Donor type: sibling or unrelated donors Conditioning intensity: myeloablative

Data Collection: Per the eligibility criteria, data will be retrospectively analyzed via and with the support of the CIBMTR database. Additional information (type of transplant program) will be obtained separately from centers contributing data to the study via survey.

4.0 STUDY ENDPOINTS:

Overall survival: time to death; patients are censored at the time of last follow-up. Treatment-related mortality: time to death without evidence of leukemia recurrence. This

event is summarized by the cumulative incidence estimate with relapse/progression as the competing risk.

Relapse: time to onset of leukemia recurrence; events will be summarized by the cumulative incidence estimate with treatment-related mortality as a competing risk.

Progression free survival: time to treatment failure (death or relapse); patients are censored at the time of last follow-up.

5.0 VARIABLES TO BE ANALYZED:

Main effect: Age at HCT: 0-14 years vs. 15-39 years vs. > 40 years.

Age at HCT: 15-21 years vs. 22-30 years vs. 31-40 years (may be recategorized based on data) – for objective #2

Period of transplant: 1990-1995 vs. 1995-2001 vs. 2002-2007 Patient-related variables:

Gender: male vs. female

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Race: Hispanic vs. non-Hispanic Whites vs. Blacks vs. Asian vs. Other Karnofsky performance score at HCT: < 90 vs. ≥ 90% Household income by zip code Distance from transplant center

Disease-related variables:

Disease status at transplant: CR1 vs. CR2 Disease type: B-cell ALL vs T-cell ALL vs ALL, NOS Cytogenetic abnormalities: Low vs. Intermediate vs. High Time from diagnosis to HCT: < 6 vs. 6-12 vs. > 12 months Time to CR1

Transplant-related variables

Period of transplant: 1990-1995 vs. 1995-2001 vs. 2002-2007 Type of transplant center: pediatric vs. adult vs. combined (2002-2007) Average # of allo transplants/year/center (2002-2007)

Allo transplants/year/center/MD (2007) Average # of allo AYA transplants/year/center (2002-2007)

Allo AYA transplants/year/center/MD (2007) Stem cell source: BM vs PBSC HLA match: HLA-identical sibling vs other related vs. URD-well matched vs. URD-

partially matched vs. URD-Mismatched GVHD prophylaxis: T-cell depletion vs. CsA+MTX vs. FK506+MTX vs. vs. Other Donor recipient CMV status: +/+ vs. +/- vs. -/+ vs. -/- Donor recipient gender match: M/M vs. M/F vs. F/M vs. F/F Conditioning regimen: TBI+Cy vs. Cy+Bu vs. TBI+Etoposide vs. Other

6.0 STUDY DESIGN:

To determine center type (adult vs. pediatric vs. combined), we will employ several methods. First, we will examine age distribution of a patients reported to us by centers to ascertain the age of their patient population. Second, we will look at data reported by centers to FACT to determine center type. For centers that are reported as combined centers, the PI or a CIBMTR staff will contact those centers individually to ask about practice patterns (e.g. some institutions with separate pediatric and adult centers report as one entity to CIBMTR and/or FACT) and patients from such institutions will be assigned accordingly. In contacting centers reported as “combined,” the PI or CIBMTR staff will ask the following questions: 1) In your inpatient transplant environment, does your center have:

a. One unit where both adult and pediatric patients receive transplants; b. Two separate units, one for adult transplant patients and one for pediatric transplant

patients c. If your answer to question 1 is “b,” then what age cut off do you use to assign

patients to adult vs pediatric services? Note: a “unit” is defined as a geographically distinct patient care area within an acute care facility, staffed by a unique set of physicians, mid-levels and nurses.

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2) In your inpatient transplant environment, does your center have: a. One “transplant team” providing care for all patients (adult and pediatric) b. Two “transplant teams,” one providing care for adult transplant patients and one

providing care for pediatric transplant patients Note: a “transplant team” is defined as a unique set of physicians, mid-levels and nurses who provide care to a group of transplant recipients in an inpatient environment.

3) In your outpatient post-transplant environment, does your center have:

a. One set of providers for all patients (adult and pediatric) b. Two sets of providers, one for adult transplant patients and one for pediatric

transplant patients Note: a “set of providers” is defined as a unique set of physicians, mid-levels and nurses who provide care to a group of transplant recipients in an outpatient environment.

4) Navneet – should we ask something about length of outpatient follow-up provided by centers? For the purposes of the analysis, centers will be categorized into groups (pediatric, adult, combined), the precise delineations of which will be determined by the PIs and Scientific Director. The chi-square test for categorical variables and the Kruskal-Wallis test for continuous variables will be used to compare patient-, disease-, and transplant-related characteristics between the three age groups. Univariate probabilities of outcomes by age group will be estimated using the Kaplan-Meier estimator for progression free survival, and cumulative incidence estimates will be used for relapse and treatment related mortality. To analyze whether OS and TRM have changed over time for AYA patients with ALL, Cox regression models will be used with year of transplant being forced into every model in order to tests its significance. Similarly, Cox models containing the year of transplant, patient’s age and interaction terms between these factors will allow us to compare changes in the outcomes between AYA and younger and older patients.

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Table 1a. Characteristics of ALL patients between the ages of 0-14 who reported an allogeneic transplant to the CIBMTR between 1990-2007. Patients were transplanted in CR1 or CR2, received a myeloablative conditioning regimen and only US centers were included.

1990-1995 1996-2001 2002-2007Characteristics N (%) N (%) N (%)Number of Patients 382 436 395Number of Centers 63 74 66Male 249 (65) 252 (58) 243 (62)Race/ethnicity of recipient White 308 (81) 295 (68) 253 (64) African-American 16 ( 4) 41 ( 9) 28 ( 7) Asian/Pacific Islander 15 ( 4) 15 ( 3) 11 ( 3) Non-White Hispanic 24 ( 6) 81 (19) 90 (23) Other/unknown/missing 19 ( 5) 4 ( 1) 13 ( 3)Karnofsky score at transplant < 90 44 (12) 57 (13) 22 ( 6) ≥ 90 333 (87) 371 (85) 327 (83) Missing 5 ( 1) 8 ( 2) 46 (12)ALL status at transplant CR1 108 (28) 141 (32) 136 (34) CR2 274 (72) 295 (68) 259 (66)Disease type B-cell 239 (63) 312 (72) 298 (75) T-cell 42 (11) 42 (10) 65 (16) Other 101 (26) 82 (19) 32 ( 8)Cytogenetic abnormalities normal 80 (21) 83 (19) 77 (19) 9-22 34 ( 9) 55 (13) 59 (15) t(4,11)+-other, no t(8,14) 19 ( 5) 43 (10) 18 ( 5) t(8,14)+-other, no t(4,11) 1 (<1) 0 2 ( 1) t(1;19)+-other 4 ( 1) 3 ( 1) 6 ( 2) hypodiploid 9 ( 2) 10 ( 2) 11 ( 3) other 81 (21) 154 (35) 141 (36) unknown 154 (40) 88 (20) 81 (21)Time from dx to tx < 6 mos 62 (16) 93 (21) 97 (25) 6-12 mos 79 (21) 68 (16) 61 (15) > 12 mos 241 (63) 275 (63) 237 (60)Graft type BM 380 (99) 408 (94) 307 (78) PBSC 2 ( 1) 28 ( 6) 88 (22)HLA match HLA-id sibling 105 (27) 97 (22) 60 (15) Well-Matched 35 ( 9) 76 (17) 165 (42) Partially matched 69 (18) 130 (30) 95 (24) Mismatched 104 (27) 94 (22) 46 (12) Other relative 67 (18) 34 ( 8) 15 ( 4) Missing 2 ( 1) 5 ( 1) 14 ( 4)

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Table 1a, Continued. 1990-1995 1996-2001 2002-2007Characteristics N (%) N (%) N (%)GVHD Prophylaxis T-cell depletion 209 (55) 242 (56) 196 (50) CSA+MTX 4 ( 1) 30 ( 7) 104 (26) FK506+MTX 146 (38) 143 (33) 50 (13) CSA+-Other 0 5 ( 1) 11 ( 3) MTX+-Other 18 ( 5) 8 ( 2) 8 ( 2) Missing 5 ( 2) 8 ( 2) 26 ( 7)Donor-recipient CMV match Neg-Neg 170 (45) 182 (42) 134 (34) Neg-Pos 67 (18) 73 (17) 112 (28) Pos-Pos 58 (15) 80 (18) 67 (17) Pos-Neg 68 (18) 94 (22) 75 (19) Missing 19 ( 5) 7 ( 2) 7 ( 2)Donor-recipient gender match M-M 143 (37) 154 (35) 147 (37) M-F 70 (18) 106 (24) 82 (21) F-M 106 (28) 98 (22) 96 (24) F-F 63 (16) 78 (18) 69 (17) Missing 0 0 1 (<1)Conditioning drug TBI+Cy 291 (76) 358 (82) 361 (91) Cy+Bu 30 ( 8) 45 (10) 4 ( 1) TBI+Etoposide 22 ( 6) 24 ( 6) 18 ( 5) TBI+-Other drug (Not Cy or Etop) 37 (10) 5 ( 1) 6 ( 2) Other 2 ( 1) 4 ( 1) 6 ( 2)Median follow-up of survivors, months 136 (13 - 214) 102 (3 - 156) 36 (3 - 86)

71


Table 1b. Characteristics of ALL patients between the ages of 15-39 who reported an allogeneic transplant to the CIBMTR between 1990-2007. Patients were transplanted in CR1 or CR2, received a myeloablative conditioning regimen and only US centers were included.

1990-1995 1996-2001 2002-2007Characteristics N (%) N (%) N (%)Number of Patients 363 415 552Number of Centers 79 107 113AYA age 15-21 153 (42) 171 (41) 188 (34) 22-30 125 (34) 139 (33) 186 (34) 31-40 85 (23) 105 (25) 178 (32)Male 229 (63) 254 (61) 354 (64)Race/ethnicity of recipient White 292 (80) 318 (77) 408 (74) African-American 14 ( 4) 21 ( 5) 23 ( 4) Asian/Pacific Islander 16 ( 4) 20 ( 5) 16 ( 3) Non-White Hispanic 20 ( 6) 53 (13) 94 (17) Other/unknown/missing 21 ( 6) 3 ( 1) 11 ( 2)Karnofsky score at transplant < 90 80 (22) 103 (25) 124 (22) ≥ 90 279 (77) 304 (73) 381 (69) Missing 4 ( 1) 8 ( 2) 47 ( 9)ALL status at transplant CR1 175 (48) 182 (44) 278 (50) CR2 188 (52) 233 (56) 274 (50)Disease type B-cell 180 (50) 269 (65) 437 (79) T-cell 64 (18) 61 (15) 83 (15) Other 119 (33) 85 (20) 32 ( 6)Cytogenetic abnormalities normal 77 (21) 82 (20) 139 (25) 9-22 45 (12) 78 (19) 135 (24) t(4,11)+-other, no t(8,14) 10 ( 3) 18 ( 4) 17 ( 3) t(8,14)+-other, no t(4,11) 4 ( 1) 5 ( 1) 3 ( 1) t(1;19)+-other 5 ( 1) 6 ( 1) 4 ( 1) hypodiploid 11 ( 3) 11 ( 3) 7 ( 1) ≥ 5 complex abn 0 5 ( 1) 1 (<1) other 62 (17) 96 (23) 126 (23) unknown 149 (41) 114 (27) 120 (22)Time from dx to tx < 6 mos 114 (31) 97 (23) 177 (32) 6-12 mos 90 (25) 116 (28) 136 (25) > 12 mos 158 (44) 202 (49) 239 (43) Missing 1 (<1) 0 0Graft type BM 358 (99) 349 (84) 219 (40) PBSC 5 ( 1) 66 (16) 333 (60)

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Table 1b, Continued. 1990-1995 1996-2001 2002-2007Characteristics N (%) N (%) N (%)HLA match HLA-id sibling 203 (56) 77 (19) 94 (17) Well-Matched 30 ( 8) 119 (29) 281 (51) Partially matched 33 ( 9) 130 (31) 131 (24) Mismatched 61 (17) 78 (19) 30 ( 5) Other relative 34 ( 9) 9 ( 2) 7 ( 1) Missing 2 ( 1) 2 (<1) 9 ( 2)GVHD Prophylaxis T-cell depletion 206 (57) 234 (56) 157 (28) CSA+MTX 9 ( 2) 71 (17) 260 (47) FK506+MTX 125 (34) 79 (19) 28 ( 5) CSA+-Other 6 ( 2) 13 ( 3) 56 (10) MTX+-Other 11 ( 3) 2 (<1) 3 ( 1) Missing 6 ( 2) 16 ( 4) 48 ( 9)Donor-recipient CMV match Neg-Neg 115 (32) 153 (37) 156 (28) Neg-Pos 76 (21) 98 (24) 158 (29) Pos-Pos 103 (28) 83 (20) 134 (24) Pos-Neg 53 (15) 64 (15) 85 (15) Missing 16 ( 4) 17 ( 4) 19 ( 3)Donor-recipient gender match M-M 133 (37) 171 (41) 228 (41) M-F 62 (17) 77 (19) 108 (20) F-M 95 (26) 82 (20) 126 (23) F-F 72 (20) 84 (20) 89 (16) Missing 1 (<1) 1 (<1) 1 (<1)Conditioning drug TBI+Cy 222 (61) 334 (80) 404 (73) Cy+Bu 44 (12) 34 ( 8) 23 ( 4) TBI+Etoposide 86 (24) 35 ( 8) 77 (14) TBI+-Other drug (Not Cy or Etop) 9 ( 2) 8 ( 2) 26 ( 5) Other 2 ( 1) 4 ( 1) 22 ( 4)Median follow-up of survivors, months 104 (5 - 224) 96 (13 - 157) 36 (3 - 89)

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Table 1c. Characteristics of ALL patients between the ages of 40-50 who reported an allogeneic transplant to the CIBMTR between 1990-2007. Patients were transplanted in CR1 or CR2, received a myeloablative conditioning regimen and only US centers were included.

1990-1995 1996-2001 2002-2007Characteristics N (%) N (%) N (%)Number of Patients 61 111 276Number of Centers 35 51 76Male 37 (61) 53 (48) 148 (54)Race/ethnicity of recipient White 56 (92) 94 (85) 240 (87) African-American 0 7 ( 6) 6 ( 2) Asian/Pacific Islander 1 ( 2) 1 ( 1) 5 ( 2) Non-White Hispanic 2 ( 3) 6 ( 5) 19 ( 7) Other/unknown/missing 2 ( 3) 3 ( 3) 6 ( 2)Karnofsky score at transplant < 90 19 (31) 31 (28) 88 (32) ≥ 90 42 (69) 74 (67) 165 (60) Missing 0 6 ( 5) 23 ( 8)ALL status at transplant CR1 48 (79) 76 (68) 210 (76) CR2 13 (21) 35 (32) 66 (24)Disease type B-cell 33 (54) 74 (67) 226 (82) T-cell 7 (11) 7 ( 6) 23 ( 8) Other 21 (34) 30 (27) 27 (10)Cytogenetic abnormalities normal 10 (16) 16 (14) 58 (21) 9-22 20 (33) 40 (36) 115 (42) t(4,11)+-other, no t(8,14) 1 ( 2) 4 ( 4) 17 ( 6) t(8,14)+-other, no t(4,11) 1 ( 2) 2 ( 2) 1 (<1) t(1;19)+-other 3 ( 5) 2 ( 2) 2 ( 1) hypodiploid 3 ( 5) 1 ( 1) 6 ( 2) ≥ 5 complex abn 0 0 2 ( 1) other 4 ( 7) 18 (16) 35 (13) unknown 19 (31) 28 (25) 40 (14)Time from dx to tx < 6 mos 35 (57) 41 (37) 137 (50) 6-12 mos 14 (23) 43 (39) 82 (30) > 12 mos 12 (20) 27 (24) 57 (21)Graft type BM 59 (97) 86 (77) 77 (28) PBSC 2 ( 3) 25 (23) 199 (72)HLA match HLA-id sibling 34 (56) 36 (32) 70 (25) Well-Matched 5 ( 8) 19 (17) 134 (49) Partially matched 12 (20) 29 (26) 53 (19) Mismatched 4 ( 7) 19 (17) 10 ( 4) Other relative 6 (10) 7 ( 6) 3 ( 1) Missing 0 1 ( 1) 6 ( 2)

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Table 1c, Continued. 1990-1995 1996-2001 2002-2007Characteristics N (%) N (%) N (%)GVHD Prophylaxis T-cell depletion 33 (54) 62 (56) 76 (28) CSA+MTX 2 ( 3) 20 (18) 140 (51) FK506+MTX 24 (39) 20 (18) 9 ( 3) CSA+-Other 1 ( 2) 4 ( 4) 28 (10) MTX+-Other 0 1 ( 1) 3 ( 1) Missing 1 ( 2) 4 ( 4) 20 ( 8)Donor-recipient CMV match Neg-Neg 17 (28) 33 (30) 75 (27) Neg-Pos 12 (20) 27 (24) 96 (35) Pos-Pos 25 (41) 31 (28) 79 (29) Pos-Neg 4 ( 7) 15 (14) 23 ( 8) Missing 3 ( 5) 5 ( 5) 3 ( 1)Donor-recipient gender match M-M 22 (36) 29 (26) 107 (39) M-F 9 (15) 37 (33) 72 (26) F-M 15 (25) 24 (22) 41 (15) F-F 15 (25) 21 (19) 56 (20)Conditioning drug TBI+Cy 41 (67) 82 (74) 162 (59) Cy+Bu 7 (11) 9 ( 8) 26 ( 9) TBI+Etoposide 11 (18) 15 (14) 55 (20) TBI+-Other drug (Not Cy or Etop) 2 ( 3) 4 ( 4) 20 ( 7) Other 0 1 ( 1) 13 ( 5)Median follow-up of survivors, months 102 (6 - 217) 100 (3 - 146) 36 (3 - 82)

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Table 1d. Characteristics of ALL patients who reported an allogeneic transplant to the CIBMTR between 1990-1995. Patients were transplanted in CR1 or CR2, received a myeloablative conditioning regimen and only US centers were included

Age at Transplant, years < 15 15-40 > 40Characteristics N (%) N (%) N (%)Number of Patients 382 363 61Number of Centers 63 79 35Hospital unit Adult 41 (11) 78 (21) 16 (26) Pediatric 165 (43) 41 (11) 0 Adult and pediatric 153 (40) 211 (58) 35 (57) Missing 23 ( 6) 33 ( 9) 10 (16)Male 249 (65) 229 (63) 37 (61)Race/ethnicity of recipient Non-Hispanic White 308 (81) 292 (80) 56 (92) African-American 16 ( 4) 14 ( 4) 0 Asian/Pacific Islander 15 ( 4) 16 ( 4) 1 ( 2) Hispanic 24 ( 6) 20 ( 6) 2 ( 3) Other/unknown/missing 19 ( 5) 21 ( 6) 2 ( 3)Karnofsky score at transplant < 90 44 (12) 80 (22) 19 (31) ≥ 90 333 (87) 279 (77) 42 (69) Missing 5 ( 1) 4 ( 1) 0ALL status at transplant CR1 108 (28) 175 (48) 48 (79) CR2 274 (72) 188 (52) 13 (21)Disease type B-cell 239 (63) 180 (50) 33 (54) T-cell 42 (11) 64 (18) 7 (11) Other 101 (26) 119 (33) 21 (34)Cytogenetics normal 80 (21) 77 (21) 10 (16) unknown 154 (40) 149 (41) 19 (31) 9-22 34 ( 9) 45 (12) 20 (33) t(4,11)+-other, no t(8,14) 19 ( 5) 10 ( 3) 1 ( 2) t(8,14)+-other, no t(4,11) 1 (<1) 4 ( 1) 1 ( 2) t(1;19)+-other 4 ( 1) 5 ( 1) 3 ( 5) hypodiploid 9 ( 2) 11 ( 3) 3 ( 5) other 81 (21) 62 (17) 4 ( 7)Time from dx to tx < 6 mos 62 (16) 114 (31) 35 (57) 6-12 mos 79 (21) 90 (25) 14 (23) > 12 mos 241 (63) 158 (44) 12 (20) Missing 0 1 (<1) 0Graft type BM 380 (99) 358 (99) 59 (97) PBSC 2 ( 1) 5 ( 1) 2 ( 3)

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Table 1d. Continued. Age at Transplant, years < 15 15-40 > 40Characteristics N (%) N (%) N (%)HLA match HLA-id sibling 105 (27) 203 (56) 34 (56) Well-Matched 35 ( 9) 30 ( 8) 5 ( 8) Partially matched 69 (18) 33 ( 9) 12 (20) Mismatched 104 (27) 61 (17) 4 ( 7) Other relative 67 (18) 34 ( 9) 6 (10) Missing 2 ( 1) 2 ( 1) 0GVHD Prophylaxis None 2 ( 1) 4 ( 1) 1 ( 2) T-cell depletion 17 ( 4) 16 ( 4) 4 ( 7) CSA+MTX 192 (50) 190 (52) 29 (48) FK506+MTX 4 ( 1) 9 ( 2) 2 ( 3) CSA+-Other 146 (38) 125 (34) 24 (39) FK506 0 6 ( 2) 1 ( 2) MTX+-Other 18 ( 5) 11 ( 3) 0 Missing 3 ( 1) 2 ( 1) 0Donor-recipient CMV match Neg-Neg 170 (45) 115 (32) 17 (28) Neg-Pos 67 (18) 76 (21) 12 (20) Pos-Pos 58 (15) 103 (28) 25 (41) Pos-Neg 68 (18) 53 (15) 4 ( 7) Missing 19 ( 5) 16 ( 4) 3 ( 5)Donor-recipient sexmatch M-M 143 (37) 133 (37) 22 (36) M-F 70 (18) 62 (17) 9 (15) F-M 106 (28) 95 (26) 15 (25) F-F 63 (16) 72 (20) 15 (25) Missing 0 1 (<1) 0Conditioning drug TBI+Cy 291 (76) 222 (61) 41 (67) Cy+Bu 30 ( 8) 44 (12) 7 (11) TBI+Etoposide 22 ( 6) 86 (24) 11 (18) TBI+-Other drug (Not Cy or Etop) 37 (10) 9 ( 2) 2 ( 3) Missing 2 ( 1) 2 ( 1) 0Median follow-up of survivors, months 136 (13 - 214) 104 (5 - 224) 102 (6 - 217)

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Table 1e. Characteristics of ALL patients who reported an allogeneic transplant to the CIBMTR between 1996-2001. Patients were transplanted in CR1 or CR2, received a myeloablative conditioning regimen and only US centers were included

Age at Transplant, years < 15 15-40 > 40Characteristics N (%) N (%) N (%)Number of Patients 436 415 111Number of Centers 74 107 51Hospital unit Adult 48 (11) 132 (32) 39 (35) Pediatric 179 (41) 58 (14) 0 Adult and pediatric 194 (44) 209 (50) 66 (59) Missing 15 ( 3) 16 ( 4) 6 ( 5)Male 252 (58) 254 (61) 53 (48)Race/ethnicity of recipient Non-Hispanic White 295 (68) 318 (77) 94 (85) African-American 41 ( 9) 21 ( 5) 7 ( 6) Asian/Pacific Islander 15 ( 3) 20 ( 5) 1 ( 1) Hispanic 81 (19) 53 (13) 6 ( 5) Other/unknown/missing 4 ( 1) 3 ( 1) 3 ( 3)Karnofsky score at transplant < 90 57 (13) 103 (25) 31 (28) ≥ 90 371 (85) 304 (73) 74 (67) Missing 8 ( 2) 8 ( 2) 6 ( 5)ALL status at transplant CR1 141 (32) 182 (44) 76 (68) CR2 295 (68) 233 (56) 35 (32)Disease type B-cell 312 (72) 269 (65) 74 (67) T-cell 42 (10) 61 (15) 7 ( 6) Other 82 (19) 85 (20) 30 (27)Cytogenetics normal 83 (19) 82 (20) 16 (14) unknown 88 (20) 114 (27) 28 (25) 9-22 55 (13) 78 (19) 40 (36) t(4,11)+-other, no t(8,14) 43 (10) 18 ( 4) 4 ( 4) t(8,14)+-other, no t(4,11) 0 5 ( 1) 2 ( 2) t(1;19)+-other 3 ( 1) 6 ( 1) 2 ( 2) hypodiploid 10 ( 2) 11 ( 3) 1 ( 1) ≥ 5 complex abnormalities 0 5 ( 1) 0 other 154 (35) 96 (23) 18 (16)Time from dx to tx < 6 mos 93 (21) 97 (23) 41 (37) 6-12 mos 68 (16) 116 (28) 43 (39) > 12 mos 275 (63) 202 (49) 27 (24)Graft type BM 408 (94) 349 (84) 86 (77) PBSC 28 ( 6) 66 (16) 25 (23)

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Table 1e. Continued. Age at Transplant, years < 15 15-40 > 40Characteristics N (%) N (%) N (%)HLA Match HLA-id sibling 97 (22) 77 (19) 36 (32) Well-Matched 76 (17) 119 (29) 19 (17) Partially matched 130 (30) 130 (31) 29 (26) Mismatched 94 (22) 78 (19) 19 (17) Other relative 34 ( 8) 9 ( 2) 7 ( 6) Missing 5 ( 1) 2 (<1) 1 ( 1)GVHD Prophylaxis None 7 ( 2) 15 ( 4) 4 ( 4) T-cell depletion 18 ( 4) 7 ( 2) 1 ( 1) CSA+MTX 224 (51) 227 (55) 61 (55) FK506+MTX 30 ( 7) 71 (17) 20 (18) CSA+-Other 143 (33) 79 (19) 20 (18) FK506 5 ( 1) 13 ( 3) 4 ( 4) MTX+-Other 8 ( 2) 2 (<1) 1 ( 1) Missing 1 (<1) 1 (<1) 0Donor-recipient CMV match Neg-Neg 182 (42) 153 (37) 33 (30) Neg-Pos 73 (17) 98 (24) 27 (24) Pos-Pos 80 (18) 83 (20) 31 (28) Pos-Neg 94 (22) 64 (15) 15 (14) Missing 7 ( 2) 17 ( 4) 5 ( 5)Donor-recipient sexmatch M-M 154 (35) 171 (41) 29 (26) M-F 106 (24) 77 (19) 37 (33) F-M 98 (22) 82 (20) 24 (22) F-F 78 (18) 84 (20) 21 (19) Missing 0 1 (<1) 0Conditioning drug TBI+Cy 358 (82) 334 (80) 82 (74) Cy+Bu 45 (10) 34 ( 8) 9 ( 8) TBI+Etoposide 24 ( 6) 35 ( 8) 15 (14) TBI+-Other drug (Not Cy or Etop) 5 ( 1) 8 ( 2) 4 ( 4) Missing 4 ( 1) 4 ( 1) 1 ( 1)Median follow-up of survivors, months 102 (3 - 156) 96 (13 - 157) 100 (3 - 146)

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Table 1f. Characteristics of ALL patients who reported an allogeneic transplant to the CIBMTR between 2002-2007. Patients were transplanted in CR1 or CR2, received a myeloablative conditioning regimen and only US centers were included.

Age at Transplant, years < 15 15-40 > 40Characteristics N (%) N (%) N (%)Number of Patients 393 552 276Number of Centers 66 113 76Hospital unit Adult 42 (11) 185 (34) 124 (45) Pediatric 173 (44) 74 (13) 8 ( 3) Adult and pediatric 176 (45) 289 (52) 137 (50) Missing 2 ( 1) 4 ( 1) 7 ( 3)Male 242 (62) 354 (64) 148 (54)Race/ethnicity of recipient Non-Hispanic white 252 (64) 408 (74) 240 (87) African-American 27 ( 7) 23 ( 4) 6 ( 2) Asian/Pacific Islander 11 ( 3) 16 ( 3) 5 ( 2) Hispanic 90 (23) 94 (17) 19 ( 7) Other/unknown/missing 13 ( 3) 11 ( 2) 6 ( 2)Karnofsky score at transplant < 90 22 ( 6) 124 (22) 88 (32) ≥ 90 326 (83) 381 (69) 165 (60) Missing 45 (11) 47 ( 9) 23 ( 8)ALL status at transplant CR1 134 (34) 278 (50) 210 (76) CR2 259 (66) 274 (50) 66 (24)Disease type B-cell 297 (76) 437 (79) 226 (82) T-cell 65 (17) 83 (15) 23 ( 8) Other 31 ( 8) 32 ( 6) 27 (10)Cytogenetics normal 77 (20) 139 (25) 58 (21) unknown 81 (21) 120 (22) 40 (14) 9-22 57 (15) 135 (24) 115 (42) t(4,11)+-other, no t(8,14) 18 ( 5) 17 ( 3) 17 ( 6) t(8,14)+-other, no t(4,11) 2 ( 1) 3 ( 1) 1 (<1) t(1;19)+-other 6 ( 2) 4 ( 1) 2 ( 1) hypodiploid 11 ( 3) 7 ( 1) 6 ( 2) ≥ 5 complex abnormalities 0 1 (<1) 2 ( 1) other 141 (36) 126 (23) 35 (13)Time from dx to tx < 6 mos 95 (24) 177 (32) 137 (50) 6-12 mos 61 (16) 136 (25) 82 (30) > 12 mos 237 (60) 239 (43) 57 (21)Graft type BM 307 (78) 219 (40) 77 (28) PBSC 86 (22) 333 (60) 199 (72)

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Table 1f. Continued. Age at Transplant, years < 15 15-40 > 40Characteristics N (%) N (%) N (%)HLA Match HLA-id sibling 60 (15) 94 (17) 70 (25) Well-Matched 164 (42) 281 (51) 134 (49) Partially matched 95 (24) 131 (24) 53 (19) Mismatched 45 (11) 30 ( 5) 10 ( 4) Other relative 15 ( 4) 7 ( 1) 3 ( 1) Missing 14 ( 4) 9 ( 2) 6 ( 2)GVHD Prophylaxis None 11 ( 3) 16 ( 3) 7 ( 3) T-cell depletion 11 ( 3) 4 ( 1) 4 ( 1) CSA+MTX 185 (47) 153 (28) 72 (26) FK506+MTX 104 (26) 260 (47) 140 (51) CSA+-Other 50 (13) 28 ( 5) 9 ( 3) FK506 11 ( 3) 56 (10) 28 (10) MTX+-Other 8 ( 2) 3 ( 1) 3 ( 1) Missing 13 ( 3) 32 ( 6) 13 ( 5)Donor-recipient CMV match Neg-Neg 132 (34) 156 (28) 75 (27) Neg-Pos 112 (28) 158 (29) 96 (35) Pos-Pos 67 (17) 134 (24) 79 (29) Pos-Neg 75 (19) 85 (15) 23 ( 8) Missing 7 ( 2) 19 ( 3) 3 ( 1)Donor-recipient sexmatch M-M 146 (37) 228 (41) 107 (39) M-F 82 (21) 108 (20) 72 (26) F-M 96 (24) 126 (23) 41 (15) F-F 68 (17) 89 (16) 56 (20) Missing 1 (<1) 1 (<1) 0Conditioning drug TBI+Cy 359 (91) 404 (73) 162 (59) Cy+Bu 4 ( 1) 23 ( 4) 26 ( 9) TBI+Etoposide 18 ( 5) 77 (14) 55 (20) TBI+-Other drug (Not Cy or Etop) 6 ( 2) 26 ( 5) 20 ( 7) Missing 6 ( 2) 22 ( 4) 13 ( 5)Median follow-up of survivors, months 36 (3 - 86) 36 (3 - 89) 36 (3 - 82)

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7.0 REFERENCES:

1. Bleyer A, Choi M, Fuller CD, Thomas CR, and SJ Wang. Relative lack of conditional survival improvement in young adults with cancer. Seminars in Oncology 2009;36(5):460-467.

2. Bleyer A. Young adult oncology: the patients and their survival challenges. CA: A Cancer Journal for Clinicians 2007;57(4):242-255.

3. Ramanujachar R, Richards S, Hann I, and D Sebb. Adolescents with acute lymphoblastic leukemia: emerging from the shadow of pediatric and adult treatment protocols. Pediatric Blood and Cancer 2006;47:748-756.

4. Pritchard MT, Butow PN, Stevens MM, and JA Duley. Understanding medication adherence in pediatric acute lymphoblastic leukemia: a review. Journal of Pediatric Hematology and Oncology 2006;28(12):816-823.

5. Bhatia S, Sather HN, Heerema NA, et al. Racial and ethnic differences in survival of children with acute lymphoblastic leukemia. Blood 2002; 100:1957-1964.

6. Tebbi CK. Treatment compliance in childhood and adolescence. Cancer suppl 1993;71:3441-3449.

7. Tamaroff MH, Festa RS, Adesman AR, et al. Therapeutic adherence to oral medication regimens by adolescents with cancer. II. Clinical and psychological correlates. Journal of Pediatrics 1992;120:812-817.

8. Stock W, La M, Sanford B, Bloomfield CD, Vardiman JW, Gaynon P, Larson RA and J Nachman. What determines the outcomes for adolescents and young adults with acute lymphoblastic leukemia treated on cooperative group protocols? A comparision of Children’s Cancer Group and Cancer and Leukemia Group B studies. Blood 2008;112(5):1646-1654.

9. Kantarjian HM and S O’Brien. Insurance policies in the United States may explain part of the outcome differences of adolescents and young adults with acute lymphoblastic leukemia treated on adult versus pediatric regimens. Blood 2009;113(8):1861,

10. Goldstone AH, Richards SM, Lazarus HM, Tallman MS, Buck G, et al. In adults with standard-risk acute lymphoblastic leukemia, the greatest benefit is achieved from a matched sibling allogeneic transplantation in first complete remission, and an autologous transplantation is less effective than conventional consolidation/maintenance chemotherapy in all patients: final results of the International ALL Trial (MRC UKALL XII/ECOG E2993). Blood 2008;111(4):1827-1833.

11. Advani AS, Hunger SP, and AK Burnett. Acute leukemia in adolescents and young adults. Seminars in Oncology 2009; 36(3):213-226.

12. Cornelissen JJ, van der Holt B, Verhoef GEG, van’t Veer MG, et al. Myeloablative allogeneic versus autologous stem cell transplantation in adult patients with acute lymphoblastic leukemia in first remission: a prospective sibling donor versus no-donor comparison. Blood 2009;113(6):1375-1382.

13. Tomblyn MB, Arora M, Baker KS, Blazar BR, Brunstein CG, et al. Myeloablative hematopoietic cell transplantation for acute lymphoblastic leukemia: analysis of graft sources and long-term outcome. Journal of Clinical Oncology 2009;27(22):3634-3641.

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CIBMTR HS08-03

CURRENT BURDEN AND FUTURE TRENDS IN THE NUMBER OF HEMATOPOIETIC CELL TRANSPLANT SURVIVORS IN THE USA

Study Chair, Navneet Majhail, MD, MS Study Statistician Assistant Scientific Director, CIBMTR and Scientific Director: Minneapolis, MN Telephone: 612-624-6982 Fax: 612-625-6919 E-mail: [email protected] Study Chair: Beth Virnig, PhD Associate Professor, Division of Health Policy and Management University of Minnesota, Minneapolis, MN Telephone: 612-624-4426 E-mail: [email protected] Study Chair: Karen Kuntz, ScD Professor, Division of Health Policy and Management University of Minnesota, Minneapolis, MN Telephone: 612-625-9333 E-mail: [email protected] Working Committee Co-Chairs: Susan Parsons, MD, MRP Tufts Medical Center 800 Washington St, #63 Boston, MA 02111 Telephone: 617-636-1450 Fax: 617-636-6280 E-mail: [email protected] Steve Joffe, MD, MPH Dana Farber Cancer Institute 44 Binney St. Boston, MA 02115 Telephone: 617-632-5295 Fax: 617-632-2270 E-mail: [email protected]

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1.0 OBJECTIVES: 1.1 Estimate the present overall number of hematopoietic cell transplant (HCT) survivors in

the USA 1.2 Estimate the present number of allogeneic and autologous HCT survivors 1.3 Estimate the future number (through 2020) of survivors of HCT for leukemia, lymphoma

and myeloma in the USA 2.0 SCIENTIFIC JUSTIFICATION:

An estimated 50-60,000 HCTs are performed worldwide each year1. The annual number of transplants has also increased progressively with time (Figure 1)1. Approximately 80-90% of all transplants are done for leukemia, lymphoma and myeloma. Introduction of newer transplant modalities and donor sources, advances in transplantation techniques and improvements in supportive care have improved outcomes following HCT with a resultant increase in the number of long term survivors. However, the cumulative number of HCT survivors since the first reports of successful transplantation in the late 1960’s is not known.

Figure 1: Annual number of hematopoietic cell transplants is progressively increasing with time There were an estimated 10.8 million cancer survivors in the USA in 2004, of which 7% had an underlying hematologic malignancy2. Since HCT is a common therapeutic modality pursued in the treatment of hematologic malignancies, a large number of prevailing HCT survivors can be expected. Estimating the current and future burden of HCT survivors has various health care planning and policy implications. HCT survivors are at an increased risk for developing a variety of medical late complications and for late mortality3-5, and require continued long-term followup for surveillance, prevention and management of late complications. An increase in the number of transplants over time with a resultant increase in the number of long term survivors will have a wide ranging impact on their health care utilization needs. A number of factors have to be considered when making predictions of future burden of cancer6. The incidence of the majority of hematologic malignancies is age dependent and the overall incidence of these diseases can be expected to increase with the ageing of our population.

84


Changes in practice and indications of transplantation can also have a significant impact on estimations of survivor burden. For example, the use of allogeneic HCT for chronic myeloid leukemia has markedly declined with the development of tyrosine kinase inhibitors. Alternatively, the utilization of HCT has increased for other diseases with the introduction of unrelated umbilical cord blood and reduced intensity conditioning regimens. Also, predictions are more accurate if previous long-term trends of incidence are known. This study will utilize incidence data from the Surveillance Epidemiology and End Results (SEER) program and prediction analysis will be limited to diseases reported to this registry (myeloma, leukemia and lymphoma).


Estimation of present HCT survivors: All patients reported to the CIBMTR through 2007 will be included in this analysis. Estimation of future HCT survivors: Patients with the following diseases will be included in this analysis: acute and chronic leukemia, myelodysplastic syndrome (MDS), lymphoma and multiple myeloma.

4.0 VARIABLES TO BE ANALYZED: Registration level data will be required for this analysis. Information on the following variables will be collected:

Date of birth

Gender

Date of initial diagnosis

Date of transplant

Cell source (peripheral blood vs. bone marrow vs. cord blood)

Donor type (autologous vs. syngeneic vs. sibling/related vs. unrelated)

Diagnosis

Followup status

5.0 STUDY DESIGN: We will used a stacked cohort simulation modeling approach to estimate the present number of HCT survivors and the future number of HCT survivors, considering patients with acute and chronic leukemia, myelodysplastic syndrome, lymphoma and multiple myeloma. For the analysis of present number of HCT survivors, besides the total number of survivors, the number of survivors by age (15 year increments), gender (male and female), HCT type (autologous and allogeneic) and common diagnoses (acute and chronic leukemia, MDS, lymphoma and multiple myeloma) will also be described. The number of current HCT survivors (i.e., in 2007) is the accumulation of patients transplanted in year 2007-x who survived x years after their transplant. We will construct the current survivorship population by simulating cohorts of patients who received HCT in each year starting in 1985. We will incorporate data on the annual number of cancers (of the specified diseases) from SEER, information on the probability of an incident case getting HCT (by type) and the

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time delay between diagnosis and HCT (from SEER-Medicare and medical literature), and survival probability curves stratified by key prognostic variables (from analysis of CIBMTR data). We will then use US population census projections and current age-specific cancer incidence to project cancer rates and HCT rates in the future. We will evaluate various assumptions about future trends in sensitivity analyses. With this model we will estimate the future number of HCT survivors, which is a combination of survivors present in 2007 (and survive to the specified year in the future) and patients who get HCT in 2007 and beyond (and survive to the specified year in the future). This study will take into account that the CIBMTR collects an estimated 50% of autologous and HLA-identical sibling and > 95% of unrelated donor HCTs performed in the US.

6.0 REFERENCES:

1. Pasquini M, Wang Z, Schneider L. CIBMTR summary slides 2007, part-I. CIBMTR

Newsletter. 2007; 13(2): 5-9. 2. Ries LAG, Melbert D, Krapcho M, et al. SEER Cancer Statistics Review, 1975-2004,

National Cancer Institute. Bethesda, MD, http://seer.cancer.gov/csr/1975_2004/, based on November 2006 SEER data submission, posted to the SEER web site, 2007 (accessed 12/13/07).

3. Bhatia S, Francisco L, Carter A, et al. Late mortality after allogeneic hematopoietic cell transplantation and functional status of long-term survivors: report from the Bone Marrow Transplant Survivor Study. Blood. 2007; 110(10): 3784-92.

4. Bhatia S, Robison LL, Francisco L, et al. Late mortality in survivors of autologous hematopoietic-cell transplantation: report from the Bone Marrow Transplant Survivor Study. Blood. 2005; 105(11): 4215-22.

5. Socié G, Stone JV, Wingard JR, et al. Long-term survival and late deaths after allogeneic bone marrow transplantation. Late Effects Working Committee of the International Bone Marrow Transplant Registry. N Engl J Med. 1999; 341(1): 14-21.

6. Bray F, Moller B. Predicting the future burden of cancer. Nat Rev Cancer. 2006; 6(1): 63-74.

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Table 1. Characteristics of U.S. patients undergoing HSCT and reporting to the CIBMTR through November 2007.

Characteristics Allogeneic AutologousNumber of patients 61,917 80,785Number of centers 220 266Age, years

Median (range) 35 (<1-87) 48 (<1-86)< 10 9324 (15) 3638 ( 5)10-19 7932 (13) 2817 ( 3)20-29 8279 (13) 5817 ( 7)30-39 10,348 (17) 11887 (15)40-49 12,686 (20) 20,633 (26)50-59 9688 (16) 22,298 (28)≥ 60 3411 ( 6) 13,606 (17)Missing 249 (<1) 89 (<1)

Male 36,310 (59) 35,742 (44)Disease code

AML 17,495 (28) 4216 ( 5)ALL 10,531 (17) 743 ( 1)CML 10,716 (17) 301 (<1)MDS 5720 ( 9) 156 (<1)Non-Hodg lymph 5614 ( 9) 21,283 (26)Hodg lymph 629 ( 1) 8162 (10)MM 1246 ( 2) 17,719 (22)Solid tumor 692 ( 1) 27,132 (34)Other * 9208 (15) 930 ( 1)

Graft type Bone marrow 37,910 (61) 12,281 (15)PBSC 20,875 (34) 68,500 (85)Cord blood 3132 ( 5) 4 (<1)

Donor HLA-id sib 27,172 (44) Other relative 4862 ( 8) Unrelated 28,073 (45) Other 451 ( 1) Missing 1359 ( 2)

Year of transplant < 1980 328 ( 1) 13 (<1)1980-84 1118 ( 2) 35 (<1)1985-89 3078 ( 5) 1325 ( 2)1990-94 9407 (15) 14,774 (18)1995-99 17,045 (28) 30,746 (38)2000-04 18,873 (30) 21,730 (27)≥ 2005 12,068 (19) 12,162 (15)

Median follow-up of survivors, months ** 46 (<1-418) 43 (<1-330)Abbreviations: MDS=myelodysplastic syndrome; HLA=human leukocyte antigen; T-del=T-cell depletion; ATG=anti-thymocyte globulin; TBI=total body irradiation. * Other disease includes: other leukemias, aplastic anemia, inherited abnormalities of erythrocyte differentiation, immune

deficiencies, inborn errors of metabolism, histiocytic disorders, inherited abnormalities of platelets, and autoimmune diseases ** Median follow-up was calculated using the KM method; the range of follow-up was calculated from all alive patients

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Number of transplant survivors by December 31st 2007:

No. of patientsNo. of survivors

by 2007Total 212264 80608By age group

0- < 18 31365 1373618- < 45 75802 2781845- < 60 74294 26708≥ 60 30803 12346

By gender Female 112361 39661Male 99903 40946

By donor type Autologous 145073 54924Related 45140 17846Unrelated 22051 7838

By disease type Acute leukemia/MDS 46997 14922CML 9355 4444Lymphoma 60490 26171Multiple myeloma 30796 15553Other 64627 19519

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Study Proposal 1111-60 Study Title: The Impact of Mandatory Reporting of Center-Specific Outcomes on Patient Selection and Center Outcomes for Allogeneic HCT in the United States N. Majhail, MD, MS, NMDP, CIBMTR, Minneapolis, MN J.D. Rizzo, MD, MS, CIBMTR, Milwaukee, WI Study Objectives: The specific aims of this study are to:

1) Evaluate whether mandatory reporting of center-specific outcomes for allogeneic hematopoietic cell transplantation (HCT) in the United States (US) has any association with trends in patient selection for allogeneic HCT by centers.

2) Evaluate whether mandatory reporting of center-specific outcomes has any association with trends in center outcomes (1-year overall survival) over time.

Scientific Justification: The CIBMTR was awarded a contract from the Health Resources and Services Administration (HRSA) in 2006 to administer the Stem Cell Therapeutic Outcomes Database (SCTOD) for the C.W. Bill Young Cell Transplantation Program. Under this Program, transplant centers in the US are required to submit a basic set of data on all allogeneic HCT to the CIBMTR. As a part of the HRSA contract, the CIBMTR submits an annual report on Center-Specific Outcomes of related and unrelated donor allogeneic HCT to HRSA that is posted on the Program website (www.bloodcell.transplant.hrsa.gov). The methodology of Center-Specific Outcomes analysis has been published by Logan et al.1 Two Center-Specific Outcomes Forums have been conducted by the CIBMTR with participation from transplant physicians and centers, payors, HRSA, and other experts to analyze reporting processes and make improvements for future reports. The 2010 Center-Specific Outcomes report included 157 centers that had performed at least one unrelated donor HCT from 2004 to 2008 and at least one related donor HCT in 2008 with followup through December 31, 2009. The final analysis included 13,244 eligible first allogeneic HCT patients. Risk-adjusted one-year survival was estimated for each center. The observed one-year survival was compared to the expected one-year survival taking into account the case-mix of patients transplanted at a given center. The public reporting of outcomes data for medical procedure may enhance institutional quality improvement efforts, stimulate standardization of procedures and innovations to improve quality and outcomes. Publically releasing performance data can stimulate quality improvement activity at the hospital level and can lead to physicians and institutions changing their clinical practices.2,3,4 However, there can be unintended consequences of public reporting of performance and outcomes data.5 In the context of allogeneic HCT, patients, referring physicians and health-care purchasers may preferentially select centers with better outcomes. Centers and transplant physicians may avoid patients with high-risk disease or comorbidities to improve their reported outcomes. In this study, we propose to evaluate the association, if any, of mandatory reporting of Center-Specific Outcomes for US centers performing allogeneic HCT with trends in selection of patients for transplantation and center outcomes over time. Due to the public reporting of outcomes data, centers may be preferentially selecting patients with a higher likelihood of better outcomes (low-risk disease or less comorbidity) to improve or maintain their overall outcomes over time. Furthermore, this effect may be more prominent in centers with lower volumes.

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Patient Eligibility Population: All patients and centers included in the 2010, 2011 and 2012 Center-Specific Outcomes reports will be included in this analysis. Collectively, these reports will include patients receiving allogeneic HCT in US centers from 2004 to 2010 for unrelated donor HCT and 2008 to 2010 for related donor HCT. The mandatory reporting of center outcomes under the SCTOD contract started in 2007 – the inclusion of patients in the above time periods will allow us to study trends before and after the implementation of these regulatory requirements. Data Requirements: Center-Specific Outcomes data files for 2010, 2011 and 2012 will be used for this analysis. Study Design: The study will consist of two parts: (1) analysis of center-specific trends over time for patient selection, and (2) analysis of center-specific trends over time for 1-year overall survival. To evaluate whether a center changed its patient case-mix over time, we will analyze time trends for the following patient selection variables which have the greatest likelihood of being controlled by the center: diagnosis, disease stage (including number of previous remissions for acute leukemia and disease chemo-sensitivity for lymphoma), presence of co-existing disease, HLA matching, recipient age, recipient Karnofsky/Lansky score at HCT. We will also evaluate trends in 1-year survival for centers. Analyses will be adjusted for risk-factors that are included in the Center-Specific Analysis (diagnosis, disease stage, donor type, coexisting disease, HLA matching, recipient age, donor age, recipient and donor gender, recipient CMV status, recipient race, recipient Karnofsky/Lansky status, prior autologous transplant, disease chemo-sensitivity for lymphoma, number of previous remissions for acute leukemia, time from diagnosis to transplant for acute leukemia, stem cell source and conditioning intensity). Analyses will account for center volume. Analyses will be stratified by patient population treated (adult vs. pediatric). References:

1. Logan BR, Nelson G and Klein JP. (2008). Analyzing center-specific outcomes in hematopoietic cell transplantation. Lifetime Data Analysis, 14: 389-404.

2. Fung CH, Lim YW, Mattke S, et al. (2008). Systematic review: The evidence that publishing patient care performance data improves quality of care. Annals of Internal Medicine, 148: 111-123.

3. Marshall MN, Shekelle PG, Leatherman S, Brook RH, et al. (2000). The public release of performance data: What do we expect to gain? A review of the evidence. JAMA, 283: 1866-1874.

4. Hibbard JH, Stockard J, Tusler M. (2005). Hospital performance reports: Impact on quality, market share, and reputation. Health Affairs, 24: 1150-1160.

5. Werner RM, Asch DA. (2005). The unintended consequences of publicly reporting quality information. JAMA, 293: 1239-1244.

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Table 1a. Characteristics of patients receiving an HLA-identical sibling transplant between 2008-2010 and reported to the CIBMTR.

2008 2009 2010

Characteristics N (%) N (%) N (%)

Number of Patients 2036 2054 2069Number of Centers 151 155 153Age of recipient at transplant Median (range) 48 (<1-74) 49 (<1-74) 50 (<1-75) ≤ 10 223 (11) 214 (10) 180 ( 9) 11-20 154 ( 8) 159 ( 8) 168 ( 8) 20-29 167 ( 8) 142 ( 7) 190 ( 9) 30-39 193 ( 9) 168 ( 8) 163 ( 8) 40-49 365 (18) 380 (19) 353 (17) 50-59 589 (29) 597 (29) 623 (30) ≥ 60 342 (17) 390 (19) 388 (19) Missing 3 (<1) 4 (<1) 4 (<1) Male 1173 (58) 1146 (56) 1183 (57)Race of recipient Hispanic 299 (15) 298 (15) 311 (15) non-Hisp Caucasian 1452 (71) 1454 (71) 1454 (70) Af-Am 164 ( 8) 168 ( 8) 156 ( 8) Asian/P.I. 91 ( 4) 99 ( 5) 111 ( 5) Other 30 ( 1) 35 ( 2) 37 ( 2)Karnofsky score pre-transplant ≥ 80 1738 (85) 1777 (87) 1801 (87) < 80 162 ( 8) 175 ( 9) 197 (10) Missing 136 ( 7) 102 ( 5) 71 ( 3)

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Table 1a, Continued. 2008 2009 2010


Disease Acute myelogenous leukemia or ANLL 729 (36) 689 (34) 684 (33) Acute lymphoblastic leukemia 341 (17) 343 (17) 332 (16) Other leukemia 100 ( 5) 120 ( 6) 107 ( 5) Chronic myelogenous leukemia 73 ( 4) 81 ( 4) 80 ( 4) Myelodysplastic/myeloprolifterative 251 (12) 270 (13) 372 (18) Other acute leukemia 23 ( 1) 13 ( 1) 18 ( 1) Non-Hodgkin lymphoma 259 (13) 268 (13) 220 (11) Hodgkin lymphoma 17 ( 1) 12 ( 1) 14 ( 1) Plasma cell disorder/Multiple Myeloma 21 ( 1) 22 ( 1) 17 ( 1) Other Malignancies 4 (<1) 9 (<1) 7 (<1) Breast Cancer 0 1 (<1) 0 Severe aplastic anemia 112 ( 6) 112 ( 5) 111 ( 5) Inherited abnormalities erythrocyt 60 ( 3) 63 ( 3) 57 ( 3) SCID and other immune system disorders 25 ( 1) 28 ( 1) 27 ( 1) Inherited abnormalities of platele 3 (<1) 0 2 (<1) Inherited disorders of metabolism 10 5 (<1) 7 (<1) Histiocytic disorders 5 (<1) 11 ( 1) 9 (<1) Autoimmune Diseases 2 (<1) 2 (<1) 0 Other, specify 1 (<1) 5 (<1) 5 (<1)Graft type BM 475 (23) 447 (22) 448 (22) PB 1542 (76) 1589 (77) 1610 (78) CB 19 ( 1) 18 ( 1) 11 ( 1)Conditioning regimen RIC/NST 543 (27) 604 (29) 659 (32) Myeloablative 1460 (72) 1411 (69) 1380 (67) Missing 33 ( 2) 39 ( 2) 30 ( 1)Conditioning drug regimen Cy+TBI+-Other 472 (23) 451 (22) 452 (22) TBI+-Oth (No Cy) 250 (12) 259 (13) 213 (10) Cy+Bu+-Other 441 (22) 393 (19) 355 (17) Cy+-Other 185 ( 9) 209 (10) 183 ( 9) Bu+LPAM+-Other 30 ( 1) 25 ( 1) 24 ( 1) Bu+-Other 404 (20) 424 (21) 538 (26) LPAM+-Other 196 (10) 248 (12) 272 (13) Missing 58 ( 3) 45 ( 2) 32 ( 2)

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Table 1a, Continued. 2008 2009 2010


Donor-Recipient sex match Donor M/Rec M 612 (30) 628 (31) 631 (30) Donor M/Rec F 434 (21) 479 (23) 453 (22) Donor F/Rec M 555 (27) 515 (25) 550 (27) Donor F/Rec F 425 (21) 425 (21) 433 (21) Missing 10 7 (<1) 2 (<1)Donor-Reipient CMV match D-/R- 524 (26) 527 (26) 489 (24) D-/R+ 429 (21) 486 (24) 497 (24) D+/R- 240 (12) 207 (10) 256 (12) D+/R+ 786 (39) 775 (38) 775 (37) Missing 57 ( 3) 59 ( 3) 52 ( 3)GVHD prophylaxis drugs None 40 ( 2) 34 ( 2) 36 ( 2) Csa (no MTX) +- Other 296 (15) 271 (13) 208 (10) Csa+MTX+-Other 366 (18) 341 (17) 329 (16) FK506 (no MTX) +- Other 384 (19) 434 (21) 443 (21) FK+MTX+-Other 811 (40) 844 (41) 949 (46) Other 99 ( 5) 83 ( 4) 69 ( 3) Missing 40 ( 2) 47 ( 2) 35 ( 2)Median follow-up of survivors, months 31 (1 - 42) 22 (1 - 30) 12 (<1 - 20)

* 142 (of 163) centers had at least one HLA-identical sibling transplant in each of the years 2008, 2009

and 2010. These 142 centers contain 6081 of the 6159 patients included in the table. Exclusion 2008 2009 2010 Total Total from table above 2036 2054 2069 6159 Total if limited to centers that did at least 5 allogeneic transplants in each year 1878 1879 1851 5608 Total if limited to centers that did at least 10 allogeneic transplants in each year 1686 1707 1692 5085

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Table 1b. Characteristics of patients who received an unrelated donor transplant between 2004-2010 and reported to the CIBMTR.

2004 2005 2006 2007 2008 2009 2010 Characteristics N (%) N (%) N (%) N (%) N (%) N (%) N (%) Number of Patients 1895 2029 2248 2348 2907 3224 3357 Number of Centers 131 131 133 136 143 142 149 Age of recipient at transplant Median (range) 36 (<1-78) 38 (<1-74) 38 (<1-75) 42 (<1-78) 44 (<1-93) 45 (<1-79) 46 (<1-83) ≤ 10 401 (21) 391 (19) 429 (19) 410 (17) 446 (15) 512 (16) 515 (15) 11-20 221 (12) 224 (11) 255 (11) 254 (11) 258 ( 9) 308 (10) 262 ( 8) 20-29 200 (11) 229 (11) 247 (11) 230 (10) 312 (11) 301 ( 9) 313 ( 9) 30-39 213 (11) 210 (10) 237 (11) 237 (10) 292 (10) 282 ( 9) 325 (10) 40-49 314 (17) 311 (15) 306 (14) 334 (14) 450 (15) 454 (14) 465 (14) 50-59 359 (19) 440 (22) 474 (21) 488 (21) 638 (22) 663 (21) 726 (22) ≥ 60 187 (10) 223 (11) 299 (13) 394 (17) 508 (17) 702 (22) 746 (22) Missing 0 1 (<1) 1 (<1) 1 (<1) 3 (<1) 2 (<1) 5 (<1) Male 1143 (60) 1147 (57) 1298 (58) 1366 (58) 1624 (56) 1902 (59) 1945 (58) Race of recipient Hispanic 178 ( 9) 171 ( 8) 211 ( 9) 228 (10) 348 (12) 323 (10) 386 (11) non-Hisp Caucasian 1490 (79) 1605 (79) 1783 (79) 1804 (77) 2239 (77) 2534 (79) 2622 (78) Af-Am 125 ( 7) 138 ( 7) 138 ( 6) 152 ( 6) 188 ( 6) 204 ( 6) 201 ( 6) Asian/P.I. 46 ( 2) 53 ( 3) 54 ( 2) 66 ( 3) 91 ( 3) 115 ( 4) 115 ( 3) Other 56 ( 3) 62 ( 3) 62 ( 3) 98 ( 4) 41 ( 1) 48 ( 1) 33 ( 1) Karnofsky score pre-transplant ≥ 80 1414 (75) 1588 (78) 1801 (80) 1874 (80) 2550 (88) 2805 (87) 2960 (88) < 80 134 ( 7) 155 ( 8) 173 ( 8) 204 ( 9) 225 ( 8) 268 ( 8) 312 ( 9) Missing 347 (18) 286 (14) 274 (12) 270 (11) 132 ( 5) 151 ( 5) 85 ( 3)

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Table 1b, Continued. 2004 2005 2006 2007 2008 2009 2010Characteristics N (%) N (%) N (%) N (%) N (%) N (%) N (%)

Disease Acute myelogenous leukemia or ANLL 669 (35) 711 (35) 766 (34) 850 (36) 1122 (39) 1192 (37) 1094 (33) Acute lymphoblastic leukemia 356 (19) 366 (18) 415 (18) 423 (18) 467 (16) 494 (15) 556 (17) Other leukemia 84 ( 4) 89 ( 4) 132 ( 6) 128 ( 5) 155 ( 5) 150 ( 5) 189 ( 6) Chronic myelogenous leukemia 175 ( 9) 131 ( 6) 112 ( 5) 103 ( 4) 121 ( 4) 112 ( 3) 142 ( 4) Myelodysplastic/myeloprolifterative 206 (11) 255 (13) 293 (13) 306 (13) 397 (14) 495 (15) 680 (20) Other acute leukemia 21 ( 1) 22 ( 1) 22 ( 1) 23 ( 1) 38 ( 1) 38 ( 1) 42 ( 1) Non-Hodgkin lymphoma 125 ( 7) 160 ( 8) 187 ( 8) 190 ( 8) 243 ( 8) 309 (10) 244 ( 7) Hodgkin lymphoma 6 (<1) 12 ( 1) 18 ( 1) 17 ( 1) 19 ( 1) 12 (<1) 12 (<1) Plasma cell disorder/Multiple Myeloma 11 ( 1) 9 (<1) 2 (<1) 5 (<1) 11 (<1) 17 ( 1) 13 (<1) Other Malignancies 9 (<1) 8 (<1) 7 (<1) 7 (<1) 4 (<1) 0 2 (<1) Breast Cancer 0 2 (<1) 0 0 1 (<1) 0 1 (<1) Severe aplastic anemia 73 ( 4) 79 ( 4) 108 ( 5) 79 ( 3) 124 ( 4) 119 ( 4) 84 ( 3) Inherited abnormalities erythrocyte 37 ( 2) 41 ( 2) 30 ( 1) 38 ( 2) 55 ( 2) 62 ( 2) 72 ( 2) SCID and other immune system disorders 42 ( 2) 62 ( 3) 64 ( 3) 80 ( 3) 61 ( 2) 89 ( 3) 99 ( 3) Inherited abnormalities of platelets 8 (<1) 2 (<1) 2 (<1) 3 (<1) 3 (<1) 9 (<1) 8 (<1) Inherited disorders of metabolism 44 ( 2) 55 ( 3) 54 ( 2) 33 ( 1) 51 ( 2) 60 ( 2) 52 ( 2) Histiocytic disorders 25 ( 1) 22 ( 1) 32 ( 1) 52 ( 2) 29 ( 1) 57 ( 2) 53 ( 2) Autoimmune Diseases 0 0 0 1 (<1) 1 (<1) 4 (<1) 2 (<1) Other, specify 4 (<1) 3 (<1) 4 (<1) 10 5 (<1) 5 (<1) 12 (<1)Graft type BM 640 (34) 560 (28) 590 (26) 569 (24) 608 (21) 666 (21) 674 (20) PB 967 (51) 1130 (56) 1261 (56) 1315 (56) 1671 (57) 1874 (58) 1999 (60) CB 288 (15) 339 (17) 397 (18) 464 (20) 628 (22) 684 (21) 684 (20)

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HLA match Well-matched unrelated 951 (50) 1031 (51) 1197 (53) 1226 (52) 1654 (57) 1885 (58) 2068 (62) Partially matched unrelated 365 (19) 377 (19) 390 (17) 397 (17) 496 (17) 555 (17) 501 (15) Mismatched unrelated 120 ( 6) 87 ( 4) 86 ( 4) 46 ( 2) 83 ( 3) 60 ( 2) 62 ( 2) Missing HLA data 171 ( 9) 195 (10) 178 ( 8) 215 ( 9) 46 ( 2) 40 ( 1) 42 ( 1) Cord Blood 288 (15) 339 (17) 397 (18) 464 (20) 628 (22) 684 (21) 684 (20)Conditioning regimen RIC/NST 424 (22) 472 (23) 565 (25) 670 (29) 789 (27) 1048 (33) 1151 (34) Myeloablative 1446 (76) 1538 (76) 1672 (74) 1665 (71) 2088 (72) 2123 (66) 2165 (64) Missing 25 ( 1) 19 ( 1) 11 (<1) 13 ( 1) 30 ( 1) 53 ( 2) 41 ( 1)Conditioning drug regimen Cy+TBI+-Other 738 (39) 717 (35) 748 (33) 739 (31) 953 (33) 954 (30) 993 (30) TBI+-Oth (No Cy) 221 (12) 192 ( 9) 264 (12) 256 (11) 330 (11) 355 (11) 381 (11) Cy+Bu+-Other 457 (24) 477 (24) 464 (21) 435 (19) 534 (18) 528 (16) 542 (16) Cy+-Other 84 ( 4) 94 ( 5) 102 ( 5) 80 ( 3) 93 ( 3) 130 ( 4) 133 ( 4) Bu+LPAM+-Other 36 ( 2) 46 ( 2) 67 ( 3) 59 ( 3) 55 ( 2) 59 ( 2) 36 ( 1) Bu+-Oth 156 ( 8) 269 (13) 344 (15) 438 (19) 552 (19) 706 (22) 750 (22) LPAM+-Oth 182 (10) 199 (10) 214 (10) 289 (12) 336 (12) 467 (14) 474 (14) Missing 21 ( 1) 35 ( 2) 45 ( 2) 52 ( 2) 54 ( 2) 25 ( 1) 48 ( 1)Donor-Recipient sex match Donor M/Rec M 624 (33) 620 (31) 737 (33) 673 (29) 1021 (35) 1212 (38) 1294 (39) Donor M/Rec F 347 (18) 410 (20) 481 (21) 438 (19) 702 (24) 754 (23) 843 (25) Donor F/Rec M 294 (16) 314 (15) 345 (15) 355 (15) 482 (17) 591 (18) 639 (19) Donor F/Rec F 246 (13) 294 (14) 304 (14) 287 (12) 491 (17) 485 (15) 560 (17) Missing 384 (20) 391 (19) 381 (17) 595 (25) 211 ( 7) 182 ( 6) 21 ( 1)

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Donor-Reipient CMV match D-/R- 432 (23) 445 (22) 499 (22) 481 (20) 793 (27) 838 (26) 885 (26) D-/R+ 502 (26) 522 (26) 588 (26) 563 (24) 876 (30) 1058 (33) 1076 (32) D+/R- 132 ( 7) 162 ( 8) 174 ( 8) 164 ( 7) 355 (12) 372 (12) 380 (11) D+/R+ 254 (13) 295 (15) 306 (14) 307 (13) 715 (25) 785 (24) 893 (27) Missing 575 (30) 605 (30) 681 (30) 833 (35) 168 ( 6) 171 ( 5) 123 ( 4)GVHD prophylaxis drugs None 24 ( 1) 43 ( 2) 62 ( 3) 85 ( 4) 46 ( 2) 57 ( 2) 54 ( 2) T-depl 9 (<1) 4 (<1) 5 (<1) 10 0 0 0 Csa (no MTX) +- Oth 433 (23) 388 (19) 405 (18) 464 (20) 591 (20) 664 (21) 695 (21) Csa+MTX+-Other 403 (21) 328 (16) 314 (14) 240 (10) 295 (10) 300 ( 9) 306 ( 9) FK506 (no MTX) +- Oth 249 (13) 344 (17) 463 (21) 550 (23) 622 (21) 696 (22) 737 (22) FK+MTX+-Other 563 (30) 718 (35) 780 (35) 775 (33) 1146 (39) 1286 (40) 1366 (41) Other 38 ( 2) 40 ( 2) 55 ( 2) 52 ( 2) 110 ( 4) 127 ( 4) 120 ( 4) Missing 176 ( 9) 164 ( 8) 164 ( 7) 172 ( 7) 97 ( 3) 94 ( 3) 79 ( 2)Median follow-up of survivors, months 72 (1 - 89) 62 (2 - 78) 50 (<1 - 66) 40 (<1 - 53) 31 (<1 - 43) 20 (2 - 29) 12 (<1 - 18)

*113 (of 158) centers had at least one unrelated donor transplant in each of the years (2004-2010). These 113 centers contain 16,749 of the 18,008 patients included in the previous table.

Exclusion 2004 2005 2006 2007 2008 2009 2010 Total

Total from table above

1895 2029 2248 2348 2907 3224 3357 18,008

Total if limited to centers that did at least 5 allogeneic transplants in each year

1757 1912 2086 2209 2696 2971 3041 16,672

Total if limited to centers that did at least 10 allogeneic transplants in each year

1659 1802 1919 2055 2467 2722 2745 15,369

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Study Proposal 1111-61 Study Title: Rates of transplantation in urban vs. rural patients: Are rural patients less likely to receive an allogeneic transplant? K. Paulson, B.Sc. (Specialist), B.Sc. (Medicine), MD, FRCPC (Internal Medicine and Hematology), Leukemia/BMT Fellow, University of Manitoba, Winnipeg, Manitoba, Canada M. Seftel, MBChB, MPH, MRCP, FRCPC, University of Manitoba, CancerCare Manitoba, Winnipeg, Manitoba, Canada D. Szwajcer, MD, MPH, FRCPC, University of Manitoba, CancerCare Manitoba, Winnipeg, Manitoba, Canada Specific Aims: Previous studies have shown that rural patients might do worse after blood and marrow transplantation than urban patients. The reasons for this are unclear, and might reflect differences in post-transplant care. However, patient selection might contribute to worse outcomes. No study has previously addressed the rate of transplantation in rural and urban patients. The main objective of this study will be to establish the rate of transplantation in rural and urban patients with AML and MDS undergoing allogeneic transplantation, and determine if there is a significant difference in utilization of transplant between rural and urban patients. Secondary outcomes include:

1. Determining the rate of transplant for patients diagnosed with AML or MDS 2. Determining the impact of other variables on the rate of transplantation in rural and urban areas,

such as socioeconomic status. 3. Determining the rate of transplant for AML and MDS by region, to determine if there is a

variation in utilization of transplant by region of the country 4. Determining if other transplant parameters are different in rural and urban patients (such as stem

cell source, conditioning regimen, and disease status at the time of transplantation) Scientific Justification: Since BMT is a highly specialized procedure, well trained and experienced laboratory personnel, nurses, and physicians are required. As such, it is usually performed in large urban centres. Some patients may live great distances away from a major transplant centre. Upon discharge from hospital, patients are often required to attend the outpatient clinic several times per week for regular assessment. The numerous follow-up visits to the outpatient clinic required places a significant burden on individuals from rural areas. Some studies have shown that patients from rural areas have inferior survival after BMT. In one study from Nebraska, rural patients undergoing autologous transplantation had a higher risk of death than urban patients. However, patients undergoing allogeneic transplantation did not have an increased risk of death. The reason for this difference was unclear, but may have related to differences in follow-up patterns after transplantation for autologous and allogeneic transplant recipients.1 We conducted a study in Manitoba, Canada, using similar methodology. Contrary to the results in the United States, there was no increase in mortality in patients undergoing either autologous or allogeneic transplantation.2 Geographic barriers might also make rural patients less likely to receive an allogeneic or autologous stem cell transplant, as other treatment options might be offered closer to their place of residence. If this is the case, the rural patients actually receiving a transplant might be only a select group of very high risk individuals. In addition, a lower rate of transplant among rural patients would be notable from a health

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policy perspective, as programs and policies could be initiated to target this at need population. We previously determined the rate of transplant amongst rural patients with Hodgkin lymphoma (HL) in Manitoba, Canada. Using cancer registry data to determine the incidence of HL, and BMT registry data to determine the rate of transplant, we found that rural patients were less likely to receive a transplant, but due to small numbers, this difference was not statistically significant.2 There has been no other published literature that has addressed this important issue. AML and MDS have been chosen as the diseases of interest. Incidence data for other types of leukemia and lymphoma are readily available in the SEER registry. CIBMTR data is complete and comprehensive for patients undergoing allogeneic transplantation, but not autologous transplantation. Thus, the focus of this study was on patients undergoing allogeneic transplantation. AML was chosen as it is the most common indication for allogeneic transplantation. In addition, although the indications for transplant in AML have evolved with the advent of molecular testing, they have been relatively consistent. MDS was chosen as a second disease of interest for several reasons. Multiple treatment options are available for patients with MDS, and the indications for transplant are less clear than with AML. The lack of clear indications and the presence of alternative therapies might lead to decreased use of transplantation in rural patients. Thus, we would hypothesize that patients from rural areas with AML and MDS will be less likely to receive an allogeneic transplantation, but the relative difference would be larger for MDS than for AML. Study Population: This study aims to integrate Surveillance Epidemiology and End Results (SEER) data in order to determine disease incidence, and CIBMTR data in order to determine the rate of transplant. The SEER registry contains population-based data on the incidence of cancer for chosen segments of the United States population. The most recent iteration of the SEER registry (SEER 17) contains data on 26.2% of the Untied States population in 480 counties in 15 states.3 These regions were chosen to reflect the broader American population. SEER data are available to interested researchers using the SEER*Stat program. All patients receiving an allogeneic transplant with an underlying diagnosis of AML or MDS reported to CIBMTR under the age of 70 in regions of the country reporting to SEER will be included. Similarly, all patients with a diagnosis of AML or MDS under the age of 70 in the SEER database will be included. Data Requirements: From the SEER Registry:

– Number of new diagnoses of AML between 2000 and 2008 in patients under the age of 70 for each county reporting to SEER

– Number of new diagnoses of MDS between 2000 and 2008 in patients under the age of 70 for each county reporting to SEER

– Rural/urban status of each county, determined by Rural-Urban Continuum Code {RUCC} – Median household income of each county, determined by census data

All of this data has already been obtained from SEER, with a spreadsheet available listing the number of new diagnoses of AML/MDS for the period of interest per county, along with the county attributes listed. From CIBMTR:

– Number of allogeneic transplants performed for AML in patients under the age of 70 between 2000 and 2008, for each county reporting to SEER (using ZIP code on TED form to determine county of residence)

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- Number of allogeneic transplants performed for MDS in patients under the age of 70 between 2000 and 2008, for each county reporting to SEER (using ZIP code on TED form to determine county of residence)

– Pertinent transplant related data, including patient gender, stem cell source (matched sibling donor or other), type of preparative regimen (myeloablative or reduced-intensity, using standard CIBMTR operational definitions), and disease status at the time of transplant (CR1, CR2, or other).

No supplemental data are required, and only TED level data is required. Study Design: This project involves integrating SEER data, to determine the incidence of AML and MDS per county, and CIBMTR data, to determine rate of transplantation. SEER data have already been collected. For each county reporting to SEER, the number of new cases of AML and MDS are available, along with the rural/urban status of that county and the median income. As mentioned, SEER data includes 480 counties in 15 states. CIBMTR does not collect data on the county of residence of patients undergoing transplant, but ZIP code is collected, and ZIP codes do correspond to a specific county. Databases listing ZIP codes by county are available from many sources, including the United States Census website. Thus, the CIBMTR database will be restricted to the ZIP codes covering the 480 counties in SEER regions. After the database is restricted, the county of residence for each patient in the CIBMTR database will be determined, using the same readily available listing ZIP codes contained in each county. At this point in time, the data will be integrated with the SEER data. Using these data, the rate of transplant for each individual county can be calculated. Finally, as each county is classified as rural or urban within the SEER registry, the rate of transplantation for all rural and all urban counties can be calculated. In a similar fashion, as SEER data include the mean income of each county, the rate of transplantation based on socioeconomic status can also be calculated. To summarize, the CIBMTR database will initially be restricted to patients under the age of 70, receiving an allogeneic transplantation for AML and MDS. A list of ZIP codes covering the 480 counties covered by SEER data will be created from publically available information. The CIBMTR data set will then further be restricted to patients residing in those ZIP codes at the time of transplant. Subsequently, using the same list of ZIP codes, patients will be categorized by their county of residency (based on their ZIP code). The number of patients in each county will be tabulated, and this figure will be integrated with the already available SEER data set. Once the numbers of cases of AML have been determined from SEER data, and the number of transplants from CIBMTR data, the rate of transplantation can be calculated. Rural and urban counties will be compared initially, using a Chi-square test to compare differences in transplant rate. As a separate analysis, the transplant rate will be compared for patients under the age of 50, and between the ages of 50 to 70. As patients under the age of 50 are less likely to have comorbidities precluding transplantation, we hypothesize that transplant rates will be higher in younger patients. As age, as a marker of comorbidity status, might be a potential reason not to pursue transplantation in a patient with high risk AML, we also hypothesize that any difference in transplant rates in younger patients between rural and urban areas will be increased in older patients. Finally, the rates of non-myeloablative transplantation, unrelated donor transplantation, and disease status

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at transplantation will be compared between rural and urban patients. References:

1. Rao K, Darrington DL, Schumacher JJ, Devetten M, Vose JM, Loberiza FR. Disparity in survival outcome after hematopoietic stem cell transplantation for hematologic malignancies according to area of primary residence. Biol Blood Marrow Transplant. 2007;13:1508-1514.

2. Paulson K, Lambert P, Bredeson C, Demers A, Nowatzki J, and Seftel MD. Does location matter? Rural vs urban outcomes after blood and marrow transplantation in a population-based Canadian cohort. Bone Marrow Transplant. 2009.

3. Surveillance, Epidemiology, and End Results (SEER) Program (www.seer.cancer.gov) Research Data (1973-2008), National Cancer Institute, DCCPS, Surveillance Research Program, Cancer Statistics Branch, released April 2011, based on the November 2010 submission. .

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Table 1a. Characteristics of patients who received an HLA-identical sibling transplant for AML or

MDS between 2000 and 2008 and reported to the CIBMTR.

AML MDSCharacteristics N (%) N (%)

Number of Patients 1476 512Number of Centers 120 93Age of recipient at transplant Median (range) 50 (<1-69) 53 (<1-69) < 20 144 (10) 32 ( 6) 20-29 127 ( 9) 17 ( 3) 30-39 149 (10) 33 ( 6) 40-49 328 (22) 116 (23) 50-59 483 (33) 207 (40) ≥ 60 245 (17) 107 (21)Male 815 (55) 304 (59)Karnofsky score at transplant ≥ 90 891 (60) 301 (59) < 90 496 (34) 167 (33) Missing 89 ( 6) 44 ( 9)Disease status at transplant AML CR1 794 (54) AML CR2 228 (15) AML ≥ CR3 12 ( 1) AML Relapse 210 (14) AML PIF 181 (12) Missing 51 ( 3) MDS Time from diagnosis to transplant, months (range) 5 (<1-313) 6 (1-253)Graft type BM 215 (15) 82 (16) PBSC 1257 (85) 428 (84) CB 4 (<1) 2 (<1)

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Table 1a, Continued. AML MDS


Conditioning regimen Traditional ablative 896 (61) 254 (50) RIC 420 (28) 193 (38) Other 160 (11) 65 (13)GHVD Prophylaxis No GVHD prophylaxis 33 ( 2) 7 ( 1) Ex vivo T-cell depletion alone 24 ( 2) 4 ( 1) Ex vivo T-cell depletion + post-tx IS 16 ( 1) 11 ( 2) CD34 selection alone 11 ( 1) 2 (<1) CD34 selection + post-tx IS 21 ( 1) 6 ( 1) Cyclophosphamide + others 2 (<1) 0 FK506 + MMF +- others 147 (10) 47 ( 9) FK506 + MTX +- others (no MMF) 490 (33) 163 (32) FK506 + others (no MTX, MMF) 101 ( 7) 38 ( 7) CSA + MMF +- others (no FK506) 138 ( 9) 54 (11) CSA + MTX +- others (no FK506, MM 309 (21) 119 (23) CSA + others (no FK506, MTX, MMF) 126 ( 9) 50 (10) Cortico + either MTX OR MMF +-Other 6 (<1) 0 Other GVHD prophylaxis 52 ( 4) 11 ( 2)ATG/Campath use ATG alone 171 (12) 62 (12) CAMPATH alone 20 ( 1) 16 ( 3) No ATG or CAMPATH 1283 (87) 433 (85) Missing 2 (<1) 1 (<1)Year of transplant 2000-04 643 (44) 255 (50) 2005-08 833 (56) 257 (50)Median follow-up of survivors, months 53 (1 - 124) 59 (2 - 135)

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Table 1b. Characteristics of patients who received an unrelated donor transplant for AML or MDS

between 2000 and 2008 and reported to the CIBMTR.

AML MDSCharacteristics N (%) N (%)

Number of Patients 4763 1751Number of Centers 148 135Age of recipient at transplant Median (range) 44 (<1-69) 50 (<1-69) < 20 900 (19) 313 (18) 20-29 567 (12) 94 ( 5) 30-39 551 (12) 159 ( 9) 40-49 930 (20) 313 (18) 50-59 1115 (23) 566 (32) ≥ 60 700 (15) 306 (17)Male 2485 (52) 1028 (59)Karnofsky score at transplant ≥ 90 2883 (61) 1025 (59) < 90 1392 (29) 521 (30) Missing 488 (10) 205 (12)Disease status at transplant AML CR1 1815 (38) AML CR2 1217 (26) AML ≥ CR3 125 ( 3) AML Relapse 899 (19) AML PIF 648 (14) Missing 59 ( 1) MDS Time from diagnosis to transplant, continuous 7 (<1-606) 8 (<1-357)Graft type BM 1501 (32) 550 (31) PBSC 2604 (55) 1023 (58) CB 658 (14) 178 (10)HLA Match Well Matched 2645 (56) 1096 (63) Partially Matched 1120 (24) 371 (21) Mismatched 734 (15) 196 (11) Missing 264 ( 6) 88 ( 5)

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Table 1b, Continued. AML MDS


Conditioning regimen Traditional ablative 3235 (68) 1095 (63) RIC 1431 (30) 619 (35) Other 97 ( 2) 37 ( 2)GHVD Prophylaxis No GVHD prophylaxis 68 ( 1) 19 ( 1) Ex vivo T-cell depletion alone 90 ( 2) 29 ( 2) Ex vivo T-cell depletion + post-tx IS 155 ( 3) 45 ( 3) CD34 selection alone 11 (<1) 2 (<1) CD34 selection + post-tx IS 25 ( 1) 5 (<1) Cyclophosphamide + others 9 (<1) 1 (<1) FK506 + MMF +- others 699 (15) 275 (16) FK506 + MTX +- others (no MMF) 1724 (36) 593 (34) FK506 + others (no MTX, MMF) 348 ( 7) 102 ( 6) CSA + MMF +- others (no FK506) 523 (11) 197 (11) CSA + MTX +- others (no FK506, MM 762 (16) 352 (20) CSA + others (no FK506, MTX, MMF) 280 ( 6) 94 ( 5) Cortico + either MTX OR MMF +-Other 8 (<1) 3 (<1) Other GVHD prophylaxis 61 ( 1) 34 ( 2)ATG/Campath use ATG + CAMPATH 3 (<1) 1 (<1) ATG alone 1493 (31) 584 (33) CAMPATH alone 197 ( 4) 71 ( 4) No ATG or CAMPATH 3066 (64) 1091 (62) Missing 4 (<1) 4 (<1)Year of transplant 2000-04 2044 (43) 750 (43) 2005-08 2719 (57) 1001 (57)Median follow-up of survivors, months 60 (3 - 137) 60 (2 - 130)

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Study Proposal 1111-63 Study Title: Survival Trends over time among White and Black patients after unrelated donor hematopoietic cell transplantation for acute leukemia and myelodysplastic syndromes. E. Denzen, MS, National Marrow Donor Program, Minneapolis, MN N. Majhail, MD, MS, National Marrow Donor Program, Center for International Blood and Marrow Transplant Research, Minneapolis, MN Specific Aims: A recent CIBMTR study has highlighted that Black patients have inferior overall survival and higher treatment related mortality (TRM) compared to White patients after matched unrelated donor (MUD) allogeneic hematopoietic cell transplantation (HCT) for acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic myeloid leukemia and myelodysplastic syndrome (MDS).1 Another recent CIBMTR study has shown similar disparities in overall survival after single unit umbilical cord blood (UCB) transplantation among Black patients compared to Whites.2 Overall survival after allogeneic HCT for AML has improved over time largely due to reductions in TRM.3 However, we do not know whether these improvements in outcomes over time have been enjoyed equally by White and Black HCT recipients.4 In this study, we would like to investigate whether racial disparities among allogeneic HCT recipients have decreased over time. Although our focus is recipients of unrelated donor transplantation where outcomes disparities have been well characterized, we will include recipients of matched sibling donor transplantation in our analysis to contrast changes in the practice and outcomes of HCT over time. Study Objectives:

1. Describe the characteristics of White and Black patients who have received sibling donor and unrelated donor HCT for AML, ALL or MDS over three 7-year time periods (1990-1996, 1997-2003, 2004-2010).

2. Describe trends over time in the utilization of MUD HCT for AML, ALL and MDS among White and Black patients (e.g., disease status at transplant, time from diagnosis to transplant, degree of HLA match, use of UCB as graft source).

3. Describe unadjusted overall-survival and TRM for White and Black patients who have received sibling donor and unrelated donor HCT for AML, ALL or MDS over three 7-year time periods (1990-1996, 1997-2003, 2004-2010).

4. For recipients of unrelated donor transplants in our cohort, describe characteristics and unadjusted survival by socioeconomic status (estimated by Zip Code of residence) for White and Black patients over three 7-year time periods (1990-1996, 1997-2003, 2004-2010).

Scientific Justification: It is well known that there are absolute differences in the rates of TRM and survival of allogeneic transplantation based on race.1,2,4 It is also known that the availability of suitable HLA-matched unrelated donors continues to be a barrier to HCT among Hispanics, Blacks and Asian Americans.4 The largest study on racial disparities among allogeneic HCT recipients has been conducted by the CIBMTR.1 In this study, Baker et al evaluated the role of race and socioeconomic status in 6,207 MUD HCT recipients with AML, ALL, CML and MDS transplanted between 1995 and 2004. Patient income was estimated from Zip Code of residence. After adjusting for socioeconomic status, Blacks had inferior overall survival and higher TRM compared to Whites while outcomes of Hispanics and Asians were comparable to that of Whites. Patients with a median annual income of $37,400 or less had a lower

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probability of overall survival and disease-free survival and higher rates of TRM, and these differences persisted after adjusting for race.1 Race and outcomes of UCB transplantation are of particular interest as UCB has the potential to increase access to HLA-matched unrelated donors for patients from specific racial and ethnic groups.4 Only one study has looked at this issue and was conducted by Ballen et al using CIBMTR data.2 Outcomes were analyzed for 612 Whites, 145 Blacks and 128 Hispanics who underwent single UCB HCT between 1995 and 2006 for ALL, AML, MDS and CML. After adjusting for important patient and disease related factors, Blacks had higher risks of overall mortality (RR 1.30, P=0.02) while survival of Hispanics was comparable to that of Whites. A significantly higher proportion of Blacks received units that were not well-matched and had a low cell dose. Although there have been improvements in outcomes of allogeneic HCT over time,3 it is not known whether all race/ethnicity groups have enjoyed similar survival benefits from innovations in HCT. Availability of suitably matched donors has been one major barrier to HCT for racial and ethnic minorities. However, the National Marrow Donor Program has invested substantial resources towards increasing the recruitment of donors from minority populations and in diversifying the registry. Furthermore, UCB transplantation which permits the use of less stringently matched grafts has the potential advantage of increasing access to HCT for patients from minority populations. Hence, it is of importance to examine whether increasing donor options and other recent advances in transplantation have narrowed the outcomes gap among White and Black HCT recipients. Increasing disparities among Whites and Blacks would raise awareness of the persisting needs of racial/ethnic minority populations, enable future studies into the factors associated with limiting survival gains (biologic, social, behavioral, etc.), and spur future interventions aimed at improving outcomes for these patients (transplant-factors, social supports, etc.). Conversely, if trends analyses show improved outcomes for these patients, future studies to examine access to and quality of donor cell sources such as UCB may be pursued. Patient Eligibility Population: The study will include matched sibling donor and unrelated donor HCT recipients for AML, ALL and MDS who received their transplant at a US center between 1990 and 2010. Adult and pediatric patients will be included. Patients could have received any conditioning regimen. Recipients of peripheral blood, bone marrow and UCB will be included. Data Requirements: The following variables will be described in addition to race (White and Black) and time period of HCT (1990-1996 and 1997-2003 and 2004-2010):

Age Gender KPS score at transplant Socioeconomic status (median household income from Zip Code of residence for unrelated donors) Diagnosis Disease status Cytogenetic risk Donor recipient gender match Donor recipient race match Time from diagnosis to transplant Stem cell source HLA match

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CMV status Conditioning regimen GVHD prophylaxis

Study Design: This study will primarily be descriptive. We will describe the characteristics of White and Black patients over the three time periods (1990-1996 and 1997-2003 and 2004-2010). For unrelated donor transplant recipients, we will also investigate changes over time stratified by socioeconomic status as determined by Zip Code of residence. Unadjusted analyses will be performed to determine overall survival and TRM over the three time periods for both race groups. For unrelated donor recipients, we will also present these outcomes stratified by socioeconomic status. We will also describe characteristics and unadjusted outcomes by age at transplantation (pediatric vs. adult). References:

1. Baker KS, Davies SM, Majhail NS, et al. Race and Socioeconomic Status Influence Outcomes of Unrelated Donor Hematopoietic Cell Transplantation. Biol Blood Marrow Transplant 2009;15(12):1543-1554.

2. Ballen KK, Klein JP, Pedersen TL, et al. Relationship of Race/Ethnicity and Survival after Single Umbilical Cord Blood Transplantation for Adults and Children with Leukemia and Myelodysplastic Syndromes. Biol Blood Marrow Transplant 2011 (In Press)

3. Horan JT, Logan BR, Agovi-Johnson MA, et al. Reducing the Risk of Transplantation Related Mortality after Allogeneic Hematopoietic Cell Transplantation: How Much Progress has Been Made? J Clin Oncol 2011;29(7):805-13.

4. Majhail NS, Nayyar S, Burton Santibañez, ME, et al. Racial Disparities in Hematopoietic Cell Transplantation in the United States. Bone Marrow Transplant 2011 (In Press).

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Table 1a. Characteristics of patients who received an unrelated donor transplant for AML, ALL

and MDS at a US center between 1990-2010.

1990-1996 1997-2003 2004-2010

White Black White Black White BlackCharacteristics N (%) N (%) N (%) N (%) N (%) N (%)

Number of Patients 2522 84 5189 286 4620 279

Number of Centers 182 41 227 93 211 100

Age of recipient at transplant

Median (range) 22 (<1-63) 16 (<1-47) 31 (0-79) 16 (0-68) 45 (<1-78) 24 (<1-70)

≤ 10 655 (26) 29 (35) 1028 (20) 105 (37) 522 (11) 72 (26)

11-20 488 (19) 25 (30) 744 (14) 73 (26) 431 ( 9) 46 (16)

20-29 444 (18) 15 (18) 751 (14) 43 (15) 522 (11) 44 (16)

30-39 430 (17) 11 (13) 766 (15) 24 ( 8) 511 (11) 27 (10)

40-49 392 (16) 4 ( 5) 910 (18) 31 (11) 775 (17) 37 (13)

50-59 110 ( 4) 0 760 (15) 9 ( 3) 1093 (24) 36 (13)

≥ 60 3 (<1) 0 230 ( 4) 1 (<1) 763 (17) 17 ( 6)

Missing 0 0 0 0 3 (<1) 0

Male 1478 (59) 50 (60) 2909 (56) 164 (57) 2604 (56) 145 (52)

Karnofsky score at transplant

< 90 891 (35) 26 (31) 1527 (29) 81 (28) 1365 (30) 59 (21)

≥ 90 1618 (64) 58 (69) 3360 (65) 187 (65) 2846 (62) 191 (68)

Missing 13 ( 1) 0 302 ( 6) 18 ( 6) 409 ( 9) 29 (10)

Disease

AML 997 (40) 28 (33) 2397 (46) 137 (48) 2530 (55) 139 (50)

ALL 1076 (43) 42 (50) 1791 (35) 111 (39) 1154 (25) 88 (32)

MDS 449 (18) 14 (17) 1001 (19) 38 (13) 936 (20) 52 (19)

Disease status at transplant

Early 529 (21) 17 (20) 1522 (29) 67 (23) 1870 (40) 94 (34)

Intermediate 871 (35) 35 (42) 1568 (30) 121 (42) 1184 (26) 100 (36)

Advanced 1079 (43) 30 (36) 1970 (38) 96 (34) 1446 (31) 79 (28)

Missing 43 ( 2) 2 ( 2) 129 ( 2) 2 ( 1) 120 ( 3) 6 ( 2)

Donor-recipient sex match

M-M 913 (36) 22 (26) 1937 (37) 73 (26) 1725 (37) 59 (21)

M-F 510 (20) 14 (17) 1249 (24) 62 (22) 1186 (26) 51 (18)

F-M 561 (22) 28 (33) 943 (18) 86 (30) 792 (17) 66 (24)

F-F 522 (21) 20 (24) 1000 (19) 56 (20) 732 (16) 74 (27)

Missing 16 ( 1) 0 60 ( 1) 9 ( 3) 185 ( 4) 29 (10)

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Table 1a, Continued. 1990-1996 1997-2003 2004-2010

White Black White Black White Black

Characteristics N (%) N (%) N (%) N (%) N (%) N (%)

Time from dx to tx

Median (range) 13 (0-248) 18 (0-163) 10 (<1-316) 13 (<1-273) 8 (<1-1140) 11 (<1-174)

< 6 mos 436 (17) 15 (18) 1427 (28) 67 (23) 1684 (36) 70 (25)

6-12 mos 823 (33) 18 (21) 1605 (31) 78 (27) 1309 (28) 90 (32)

> 12 mos 1260 (50) 51 (61) 2137 (41) 141 (49) 1585 (34) 116 (42)

Missing 3 (<1) 0 20 0 42 ( 1) 3 ( 1)

Graft type

BM 2438 (97) 73 (87) 3391 (65) 181 (63) 1203 (26) 79 (28)

PBSC 11 (<1) 0 1314 (25) 28 (10) 2934 (64) 111 (40)

CB 73 ( 3) 11 (13) 484 ( 9) 77 (27) 483 (10) 89 (32)

HLA Match

Well matched 424 (17) 1 ( 1) 1919 (37) 45 (16) 2739 (59) 72 (26)

Partially matched 852 (34) 22 (26) 1671 (32) 72 (25) 944 (20) 78 (28)

Mismatched 1086 (43) 49 (58) 752 (14) 89 (31) 171 ( 4) 36 (13)

Cord Blood 73 ( 3) 11 (13) 484 ( 9) 77 (27) 483 (10) 89 (32)

Missing 87 ( 3) 1 ( 1) 363 ( 7) 3 ( 1) 283 ( 6) 4 ( 1)

Donor-recipient CMV match

Neg-Neg 882 (35) 17 (20) 1711 (33) 53 (19) 1267 (27) 31 (11)

Neg-Pos 681 (27) 28 (33) 1392 (27) 60 (21) 1451 (31) 60 (22)

Pos-Pos 442 (18) 24 (29) 909 (18) 63 (22) 822 (18) 78 (28)

Pos-Neg 440 (17) 12 (14) 737 (14) 50 (17) 471 (10) 28 (10)

Missing 77 ( 3) 3 ( 4) 440 ( 8) 60 (21) 609 (13) 82 (29)

Conditioning regimen

Myeloablative 2522 84 4451 (86) 264 (92) 3136 (68) 216 (77)

RIC 702 (14) 22 ( 8) 1445 (31) 61 (22)

Other 36 ( 1) 0 39 ( 1) 2 ( 1)

Conditioning drug

TBI+Cy 1924 (76) 62 (74) 3013 (58) 188 (66) 1670 (36) 120 (43)

Cy+Bu 383 (15) 9 (11) 1035 (20) 29 (10) 959 (21) 55 (20)

TBI+Etoposide 35 ( 1) 3 ( 4) 79 ( 2) 8 ( 3) 147 ( 3) 9 ( 3)

Other 175 ( 7) 8 (10) 1010 (19) 60 (21) 1780 (39) 93 (33)

Missing 5 (<1) 2 ( 2) 52 ( 1) 1 (<1) 64 ( 1) 2 ( 1)

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Table 1a, Continued. 1990-1996 1997-2003 2004-2010



GHVD Prophylaxis

No GVHD prophylaxis 11 (<1) 0 35 ( 1) 0 40 ( 1) 2 ( 1)

Ex vivo T-cell depletion alone 206 ( 8) 10 (12) 228 ( 4) 21 ( 7) 75 ( 2) 7 ( 3)

Ex vivo T-cell depletion + post-tx IS

380 (15) 11 (13) 408 ( 8) 31 (11) 99 ( 2) 7 ( 3)

CD34 selection alone 0 0 8 (<1) 1 (<1) 11 (<1) 1 (<1)

CD34 selection + post-tx IS 0 0 28 ( 1) 0 25 ( 1) 1 (<1)

Cyclophosphamide +/- others 0 0 0 0 14 (<1) 0

FK506 + MMF +/- others 1 (<1) 0 169 ( 3) 10 ( 3) 676 (15) 56 (20)

FK506 + MTX +/- others (no MMF)

120 ( 5) 8 (10) 876 (17) 47 (16) 1600 (35) 88 (32)

FK506 +/- others (no MTX, no MMF)

38 ( 2) 2 ( 2) 170 ( 3) 14 ( 5) 259 ( 6) 19 ( 7)

CSA + MMF +/- others (no FK506)

0 0 311 ( 6) 9 ( 3) 495 (11) 45 (16)

CSA + MTX +/- others (no FK506 or MMF)

1528 (61) 40 (48) 2368 (46) 86 (30) 935 (20) 28 (10)

CSA +/- others (no FK506, MTX or MMF)

216 ( 9) 12 (14) 542 (10) 65 (23) 328 ( 7) 24 ( 9)

Cortico + either MTX OR MMF +/- Other

11 (<1) 0 14 (<1) 2 ( 1) 6 (<1) 0

Other GVHD prophylaxis 11 (<1) 1 ( 1) 32 ( 1) 0 57 ( 1) 1 (<1)

ATG/Campath Use

ATG + CAMPATH 2 (<1) 0 2 (<1) 0 1 (<1) 1 (<1)

ATG alone 646 (26) 28 (33) 1986 (38) 156 (55) 1595 (35) 114 (41)

CAMPATH alone 59 ( 2) 0 194 ( 4) 8 ( 3) 224 ( 5) 18 ( 6)

No ATG or CAMPATH 1812 (72) 56 (67) 2999 (58) 122 (43) 2799 (61) 146 (52)

Missing 3 (<1) 0 8 (<1) 0 1 (<1) 0

Median follow-up of survivors, months 161 (7 - 249) 87 (47 - 244) 96 (2 - 173) 95 (5 - 149) 56 (1 - 89) 57 (2 - 79)

IS = Immune Suppression

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Table 1b. Characteristics of patients who received an HLA-identical sibling transplant for AML,

ALL and MDS at a US center between 1990-2010.

1990-1996 1997-2003 2004-2010



Number of Patients 5155 159 3162 104 1671 70

Number of Centers 261 61 208 64 151 42

Age of recipient at transplant

Median (range) 29 (<1-67) 31 (<1-57) 37 (<1-75) 38 (<1-61) 45 (<1-75) 45 (<1-68)

≤ 10 783 (15) 29 (18) 379 (12) 15 (14) 111 ( 7) 5 ( 7)

11-20 846 (16) 26 (16) 448 (14) 19 (18) 198 (12) 5 ( 7)

20-29 1026 (20) 22 (14) 443 (14) 10 (10) 206 (12) 6 ( 9)

30-39 1159 (22) 42 (26) 463 (15) 12 (12) 195 (12) 10 (14)

40-49 987 (19) 35 (22) 639 (20) 27 (26) 318 (19) 14 (20)

50-59 330 ( 6) 5 ( 3) 601 (19) 20 (19) 448 (27) 23 (33)

≥ 60 23 (<1) 0 189 ( 6) 1 ( 1) 195 (12) 7 (10)

Missing 1 (<1) 0 0 0 0

Male 2997 (58) 79 (50) 1752 (55) 53 (51) 973 (58) 35 (50)

Karnofsky score at transplant

< 90 1432 (28) 48 (30) 957 (30) 42 (40) 437 (26) 22 (31)

≥ 90 3662 (71) 108 (68) 2131 (67) 58 (56) 1151 (69) 42 (60)

Missing 61 ( 1) 3 ( 2) 74 ( 2) 4 ( 4) 83 ( 5) 6 ( 9)

Disease

AML 2782 (54) 101 (64) 1718 (54) 59 (57) 975 (58) 43 (61)

ALL 1757 (34) 42 (26) 863 (27) 32 (31) 400 (24) 16 (23)

MDS 616 (12) 16 (10) 581 (18) 13 (12) 296 (18) 11 (16)

Disease status at transplant

Early 2548 (49) 75 (47) 1520 (48) 43 (41) 901 (54) 44 (63)

Intermediate 1041 (20) 33 (21) 623 (20) 23 (22) 276 (17) 8 (11)

Advanced 1447 (28) 47 (30) 897 (28) 33 (32) 440 (26) 12 (17)

Missing 119 ( 2) 4 ( 3) 122 ( 4) 5 ( 5) 54 ( 3) 6 ( 9)

Donor-recipient sex match

M-M 1647 (32) 45 (28) 963 (30) 25 (24) 530 (32) 18 (26)

M-F 1145 (22) 43 (27) 754 (24) 25 (24) 356 (21) 9 (13)

F-M 1335 (26) 34 (21) 777 (25) 27 (26) 420 (25) 16 (23)

F-F 1004 (19) 37 (23) 651 (21) 25 (24) 325 (19) 26 (37)

Missing 24 (<1) 0 17 ( 1) 2 ( 2) 40 ( 2) 1 ( 1)

112


Table 1b, Continued. 1990-1996 1997-2003 2004-2010



Time from dx to tx

Median (range) 6 (<1-991) 6 (1-85) 6 (<1-321) 7 (<1-207) 6 (<1-313) 6 (1-109)

< 6 mos 2393 (46) 77 (48) 1535 (49) 44 (42) 886 (53) 40 (57)

6-12 mos 1410 (27) 40 (25) 765 (24) 28 (27) 383 (23) 8 (11)

> 12 mos 1349 (26) 42 (26) 860 (27) 32 (31) 392 (23) 22 (31)

Missing 3 (<1) 0 2 (<1) 0 10 ( 1) 0

Graft type

BM 4761 (92) 151 (95) 1334 (42) 39 (38) 338 (20) 16 (23)

PBSC 377 ( 7) 7 ( 4) 1800 (57) 63 (61) 1330 (80) 54 (77)

CB 17 (<1) 1 ( 1) 28 ( 1) 2 ( 2) 3 (<1) 0

Donor-recipient CMV match

Neg-Neg 1499 (29) 26 (16) 835 (26) 15 (14) 402 (24) 9 (13)

Neg-Pos 959 (19) 24 (15) 533 (17) 20 (19) 304 (18) 15 (21)

Pos-Pos 1871 (36) 86 (54) 1294 (41) 53 (51) 703 (42) 35 (50)

Pos-Neg 561 (11) 15 ( 9) 319 (10) 7 ( 7) 157 ( 9) 6 ( 9)

Missing 265 ( 5) 8 ( 5) 181 ( 6) 9 ( 9) 105 ( 6) 5 ( 7)

Conditioning regimen

Myeloablative 5155 159 2530 (80) 81 (78) 1168 (70) 44 (63)

RIC 509 (16) 17 (16) 421 (25) 22 (31)

Other 123 ( 4) 6 ( 6) 82 ( 5) 4 ( 6)

Conditioning drug

TBI+Cy 2342 (45) 64 (40) 1000 (32) 34 (33) 490 (29) 13 (19)

Cy+Bu 2087 (40) 71 (45) 1303 (41) 31 (30) 579 (35) 17 (24)

TBI+Etoposide 324 ( 6) 6 ( 4) 141 ( 4) 9 ( 9) 74 ( 4) 7 (10)

Other 365 ( 7) 16 (10) 602 (19) 25 (24) 441 (26) 29 (41)

Missing 37 ( 1) 2 ( 1) 116 ( 4) 5 ( 5) 87 ( 5) 4 ( 6)

113


Table 1b, Continued. 1990-1996 1997-2003 2004-2010



GHVD Prophylaxis

No GVHD prophylaxis 34 ( 1) 1 ( 1) 16 ( 1) 3 ( 3) 28 ( 2) 1 ( 1)

Ex vivo T-cell depletion alone 218 ( 4) 5 ( 3) 25 ( 1) 3 ( 3) 25 ( 1) 0

Ex vivo T-cell depletion + post- tx IS

241 ( 5) 5 ( 3) 32 ( 1) 0 23 ( 1) 0

CD34 selection alone 1 (<1) 0 13 (<1) 2 ( 2) 3 (<1) 0

CD34 selection + post-tx IS 0 0 42 ( 1) 1 ( 1) 5 (<1) 0

FK506 + MMF +/- others 0 0 40 ( 1) 2 ( 2) 104 ( 6) 10 (14)

FK506 + MTX +/- others (no MMF)

31 ( 1) 0 200 ( 6) 11 (11) 379 (23) 30 (43)

FK506 + others (no MTX or MMF)

30 ( 1) 4 ( 3) 72 ( 2) 5 ( 5) 72 ( 4) 3 ( 4)

CSA + MMF +/- others (no FK506)

0 0 154 ( 5) 5 ( 5) 113 ( 7) 4 ( 6)

CSA + MTX +/- others (no FK506 or MMF)

3244 (63) 88 (55) 1945 (62) 56 (54) 751 (45) 15 (21)

CSA + others (no FK506, MTX or MMF)

1149 (22) 49 (31) 558 (18) 14 (13) 136 ( 8) 4 ( 6)

Cortico + either MTX OR MMF +/- Other

42 ( 1) 2 ( 1) 4 (<1) 0 8 (<1) 0

Other GVHD prophylaxis 165 ( 3) 5 ( 3) 61 ( 2) 2 ( 2) 24 ( 1) 3 ( 4)

ATG/Campath use

ATG + CAMPATH 1 (<1) 0 0 0 0 0

ATG alone 75 ( 1) 2 ( 1) 292 ( 9) 10 (10) 159 (10) 8 (11)

CAMPATH alone 8 (<1) 0 44 ( 1) 3 ( 3) 42 ( 3) 2 ( 3)

No ATG or CAMPATH 5062 (98) 157 (99) 2823 (89) 91 (88) 1469 (88) 60 (86)

Missing 9 (<1) 0 3 (<1) 0 1 (<1) 0

Median follow-up of survivors, months

120 (2 - 249) 122 (7 - 219) 87 (1 - 173) 94 (12 - 153) 48 (<1 - 90) 47 (3 - 73)

IS = Immune Suppression

114

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Not for publication or presentation · 2014. 1. 14. · Not for publication or presentation DRAFT AGENDA CIBMTR WORKING COMMITTEE FOR HEALTH POLICY AND PSYCHOSOCIAL ISSUES San Diego,