Assessment of Time-to-Treatment Initiation and Survival in a … · Medicaid 435 077 (37.3) 53 502 (57.8) 6029 (4.6) 17 371 (2.0) Medicare 67 379 (5.8) 3215 (3.5) 83 790 (64.2) 364

Original Investigation | Oncology

Assessment of Time-to-Treatment Initiation and Survival in a Cohort of PatientsWith Common CancersEugene B. Cone, MD; Maya Marchese, MS; Marco Paciotti, MD; David-Dan Nguyen, MPH; Junaid Nabi, MD; Alexander P. Cole, MD; George Molina, MD, MPH;Rose L. Molina, MD, MPH; Christina A. Minami, MD, MS; Lorelei A. Mucci, MPH, ScD; Adam S. Kibel, MD; Quoc-Dien Trinh, MD

Abstract

IMPORTANCE Resource limitations because of pandemic or other stresses on infrastructurenecessitate the triage of time-sensitive care, including cancer treatments. Optimal time to treatmentis underexplored, so recommendations for which cancer treatments can be deferred are often basedon expert opinion.

OBJECTIVE To evaluate the association between increased time to definitive therapy and mortalityas a function of cancer type and stage for the 4 most prevalent cancers in the US.

DESIGN, SETTING, AND PARTICIPANTS This cohort study assessed treatment and outcomeinformation from patients with nonmetastatic breast, prostate, non-small cell lung (NSCLC), andcolon cancers from 2004 to 2015, with data analyzed January to March 2020. Data on outcomesassociated with appropriate curative-intent surgical, radiation, or medical therapy were gatheredfrom the National Cancer Database.

EXPOSURES Time-to-treatment initiation (TTI), the interval between diagnosis and therapy, usingintervals of 8 to 60, 61 to 120, 121 to 180, and greater than 180 days.

MAIN OUTCOMES AND MEASURES 5-year and 10-year predicted all-cause mortality.

RESULTS This study included 2 241 706 patients (mean [SD] age 63 [11.9] years, 1 268 794 [56.6%]women, 1 880 317 [83.9%] White): 1 165 585 (52.0%) with breast cancer, 853 030 (38.1%) withprostate cancer, 130 597 (5.8%) with NSCLC, and 92 494 (4.1%) with colon cancer. Median(interquartile range) TTI by cancer was 32 (21-48) days for breast, 79 (55-117) days for prostate, 41(27-62) days for NSCLC, and 26 (16-40) days for colon. Across all cancers, a general increase in the5-year and 10-year predicted mortality was associated with increasing TTI. The most pronouncedmortality association was for colon cancer (eg, 5 y predicted mortality, stage III: TTI 61-120 d, 38.9%vs. 181-365 d, 47.8%), followed by stage I NSCLC (5 y predicted mortality: TTI 61-120 d, 47.4% vs181-365 d, 47.6%), while survival for prostate cancer was least associated (eg, 5 y predicted mortality,high risk: TTI 61-120 d, 12.8% vs 181-365 d, 14.1%), followed by breast cancer (eg, 5 y predictedmortality, stage I: TTI 61-120 d, 11.0% vs. 181-365 d, 15.2%). A nonsignificant difference in treatmentdelays and worsened survival was observed for stage II lung cancer patients—who had the highestall-cause mortality for any TTI regardless of treatment timing.

CONCLUSIONS AND RELEVANCE In this cohort study, for all studied cancers there was evidencethat shorter TTI was associated with lower mortality, suggesting an indirect association betweentreatment deferral and mortality that may not become evident for years. In contrast to current

(continued)

Key PointsQuestion What is the associationbetween delays in treatment initiation

for common cancers, as are necessary in

resource-limited settings and pandemic

conditions, with mortality?

Findings In this cohort study including2 241 706 patients with breast, prostate,

non-small cell lung, and colon cancer,

generally higher all-cause mortality was

associated with increasing time to

treatment, although the degree varied

by cancer type and stage. Patients with

colon and lung cancer had the highest

mortality associated with increased time

to treatment.

Meaning These findings emphasize theimportance of timely cancer treatment,

and, in contrast to current pandemic-

related guidelines, support more

prompt definitive treatment for

intermediate-risk and high-risk

prostate cancer.

+ Invited Commentary+ Supplemental contentAuthor affiliations and article information arelisted at the end of this article.

Open Access. This is an open access article distributed under the terms of the CC-BY License.

JAMA Network Open. 2020;3(12):e2030072. doi:10.1001/jamanetworkopen.2020.30072 (Reprinted) December 14, 2020 1/13

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Abstract (continued)

pandemic-related guidelines, these findings support more timely definitive treatment forintermediate-risk and high-risk prostate cancer.

JAMA Network Open. 2020;3(12):e2030072. doi:10.1001/jamanetworkopen.2020.30072

Introduction

The coronavirus disease 2019 (COVID-19) pandemic virus has overwhelmed health care systems,forcing redistribution of supplies, personnel, and treatments.1-3 To efficiently utilize scarce resourceswhile minimizing exposure risk to patients and staff, oncologists have been urged to triage cancercare.4 Such deferral of care is difficult to implement as cancer remains a leading cause of death5 andearly intervention can improve patient outcomes.6

Lengthy time to treatment initiation (TTI—the period between diagnosis and the start ofdefinitive treatment) has previously been associated with an absolute increased risk of mortality,from 1.2% to 3.2% per week of delayed treatment in cancers such as lung, kidney, and pancreas,7

with inconsistent effects over time.8 For breast cancer, increasing TTI has been associated withworse survival, especially for underserved patients.9-11 For head and neck cancers, TTI beyond 2months was associated with a 3-fold increase in mortality.12-15 A systematic review of symptomaticcancers found some association between shorter TTI and better clinical outcomes (primarily survival)for breast, colorectal, head and neck, and testicular cancers, but the findings were limited becauseof poor quality studies and heterogeneous methodology.6 As such, triaging cancer patients presentsimplementation challenges as there are no preexisting guidelines on optimal TTI across diseases, andguidelines released in response to the COVID pandemic were largely based on expert opinion.4,16

Understanding the impact of TTI on survival is crucial in allocating resources efficiently,especially when unforeseeable limitations arise—either because of external pressures such aspandemics, or internal factors such as underfunding, understaffing, or supply chain constraints. Wetherefore evaluated the association between increasing time to definitive therapy and overallsurvival as a function of cancer type, stage, and treatment modality for patients treated with curativeintent for nonmetastatic disease in the 4 most prevalent cancers in the US: breast cancer, prostatecancer, non-small cell lung cancer (NSCLC), and colon cancer.17 We hypothesized that increased TTIwould be negatively associated with overall survival for all cancers and that the effect size would varyby cancer type and stage. As we only focused on National Comprehensive Cancer Network (NCCN)guideline-approved treatments, we assumed that outcomes would not vary by treatment modality.

Methods

Data SourceWe used the National Cancer Database (NCDB), a nationwide oncology-specific databaseadministered by the Commission on Cancer and the American Cancer Society. The NCDB capturesover 70% of cancer diagnoses in the US, including over 29 million individual cancers from over 1500accredited facilities, which are abstracted by trained reviewers.18,19 This research was approved bythe Partners Healthcare institutional review board, and was exempted from informed consentrequirements because it used deidentified data from NCDB files; the manuscript reporting ourfindings was written in adherence with the Strengthening the Reporting of Observational Studies inEpidemiology (STROBE) reporting guideline.

Patient PopulationFrom January through March 2020, using NCDB years 2004 to 2015, we identified patientsdiagnosed with nonmetastatic breast cancer, prostate cancer, NSCLC, and colon cancer at stages

JAMA Network Open | Oncology Assessment of Time-to-Treatment Initiation and Survival in a Cohort of Patients With Common Cancers



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eligible for definitive therapy per era-appropriate NCCN guidelines (complete eligibility criteria ineAppendix 1 in the Supplement). These cancers were selected as they are the 4 most common UScancers, they span a range of clinical aggression, they are treated in most accredited cancer facilities,and patients are eligible for definitive therapy via a variety of modalities.18,20 Stage III lung cancerwas not included as there is no validated NCDB method to determine patient eligibility for definitivetherapy. Prostate cancer was defined by NCCN risk category per standard of practice in the US. Stage0 colon cancer was excluded as most patients are adequately treated via diagnostic polyp removal.

ExposureThe exposure was TTI—the time in days from the date of diagnosis to receipt of definitive therapy forthe patient’s disease. Receipt of definitive therapy was defined for each cancer subtype using 2004to 2015 era-appropriate NCCN guidelines reviewed by cancer-specific disease experts (completeeligibility criteria in eAppendix 2 in the Supplement). TTI was a categorical variable with 4 levels: 8 to60, 61 to 120, 121 to 180, and greater than 180 days. These time periods were chosen a priori asclinically useful and reflective of practice patterns. For example, a decision to defer all treatment fora given cancer and stage for a 2-month period during a pandemic is more readily implemented andimpactful than a decision to stop treatment for 1 or 2 weeks on a hospital level. Patients with TTIwithin 1 week of diagnosis were excluded, as this may not represent elective surgery, as were thosewith TTI greater than 1 year because of the small sample sizes and validity concerns.

Variables of InterestWe abstracted clinical demographic variables, which included age at diagnosis, race (as defined byNCDB), sex, facility type, facility county, county-level median household income, residence type,county-level median education level, diagnosis year, insurance status, and Charlson-Deyo score to beused as model covariates. Tumor-specific variables were also collected, including American JointCommittee on Cancer clinical stage (AJCC Cancer Staging Manual, Eighth Edition), grade, histology(where appropriate), and receptor status (where appropriate). Modality of any treatment receivedwas abstracted (ie, surgery, chemotherapy, radiation therapy) and used to define definitive therapy,as was time from biopsy-based diagnosis to receipt of treatments. Given disparities in bothpreexisting cancer outcomes and the impact of the pandemic on racial minority groups,21,22 we alsoexamined whether the association between TTI and predicted mortality varied by race.

Outcome MeasureThe primary outcome was all-cause mortality. The estimates of interest were predicted 5-year and10-year all-cause mortality. We accepted as a limitation that we would not be able to identify thereason for delay, and that this could introduce bias.

Statistical AnalysisTo assess the association between TTI and predicted all-cause mortality for each cancer type, we fita Cox proportional hazards model for each cancer and stage (assuming each stage representedseparate populations) with TTI as the predictor, adjusting for the aforementioned covariates andclustering standard errors by facility, while testing to ensure proportional hazards assumptions weremet.23 We tested for differences in TTI hazards, using the 8-to-60–day TTI group as referent andtesting each 60-day cohort against it. We then used each model’s estimated log hazard ratiocoefficients to compute mean predicted mortality outcomes for patients in each level of TTI by takingthe linear combination of the model estimates set at each level of TTI and time and the mean of allcovariates. Deriving predicted outcomes, while setting the covariate values at their mean, allowed usto estimate the mean difference in outcomes for each patient under different TTI while conservingtheir clinical and demographic characteristics. The mean predicted outcomes for each time point–TTIcombination were then transformed to the predicted probability of mortality at that TTI and timepoint. We then extracted the 5-year and 10-year predicted mortality probabilities for each TTI.




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Predicted mortality was used, based on model estimates taken from the actual mortality data of thecohort within the NCDB, to provide a smoothed curve as a continuous function of time that couldbe easily interpreted by clinicians and policymakers. We accepted that groups with small sample sizeswould yield less precise estimates but countered this by choosing highly incident cancers yieldinglarge cohort sizes.

Results

We included 2 241 706 patients (mean [SD] age of 63 [11.9]; 1 268 794 [56.6%] women; and1 880 317 [83.9%] White) (Figure 1). By disease, 1 165 585 (52.0%) patients had breast cancer,853 030 (38.1%) had prostate cancer, 130 597 (5.8%) had NSCLC, and 92 494 (4.1%) had coloncancer. Full clinical demographic characteristics can be found in Table 1. Median (interquartile range[IQR]) TTI was 32 (21-48) days for breast, 79 (55-117) days for prostate, 41 (27-62) days for NSCLC,and 26 (16-40) days for colon (medians with IQRs by cancer with stage can be found in Table 2).

The predicted 5-year and 10-year mortality rates were greatest for stage II NSCLC with TTI 61 to120 days (62.0% and 81.2%, respectively). The predicted 5-year and 10-year mortality rates werelowest for low-risk prostate cancer patients treated within 60 days (4.9% and 17.3%, respectively).While analysis of all-stage prostate and breast did not reveal any association with delay, by-stageanalysis demonstrated associations of high-risk and intermediate-risk prostate and stage I and IIbreast cancers with TTI of 61 to 120 days, and all-stage breast cancers with TTI greater than 121 days.Generally, increasing TTI and advanced stage and risk was associated with greater predictedmortality across all cancers (eg, predicted mortality: stage III breast cancer at TTI 181-365 d, 32.7% vsstage 0 breast cancer at TTI 8-60 d, 9.6%). Sensitivity analysis using 30-day intervals found nodifference in trends by disease. Predicted 5-year and 10-year mortality by disease, stage, and TTI canbe found in Table 3, with predicted mortality curves in Figures 2 and 3 (all differences significantexcept low-risk prostate cancer and stage II lung cancer). The most pronounced mortality associationwas for colon cancer (eg, 5 y predicted mortality, stage III: TTI 61-120 d, 38.9% vs. 181-365 d, 47.8%),followed by stage I NSCLC (5 y predicted mortality: TTI 61-120 d, 47.4% vs 181-365 d, 47.6%), whilesurvival for prostate cancer was least associated (eg, 5 y predicted mortality, high risk: TTI 61-120 d,12.8% vs 181-365 d, 14.1%), followed by breast cancer (eg, 5 y predicted mortality, stage I: TTI 61-120d, 11.0% vs. 181-365 d, 15.2%). The interaction between TTI and race was not significant for mostcancer stages tested.

Significance was found with TTI 8 to 60 days as referent only for stage III colon cancer at TTI 61to 120 days (34.6% vs 38.9%; P = .03); intermediate-risk prostate cancer at TTI 121 to 180 days (7.0%

Figure 1. Flowchart of Patient Selection for Analysis

6 059 569 Patients diagnosed with cancer, 2004-20152 459 779 Breast

810 062 Colon

1 407 364 Non-small cell lung1 382 364 Prostate

2 241 706 Patients included1 165 585 Breast cancer

92 494 Colon cancer

853 030 Prostate cancer130 597 Non-small cell lung cancer

3 817 863 Patients excluded2 150 207 Ineligible, missing, or unknown clinical staging or histology

547 With no follow-up data

1 048 427 With metastatic cancer618 682 Did not receive definitive treatment or received treatment within

365 d from diagnosis




Table 1. Baseline Clinical Demographic Characteristics of Nonmetastatic Cancer Patients in NCDB Database,2004-2015

Characteristics

Patients, No. (%)Breast(n = 1 165 585)

Colon(n = 92 494)

NSC lung(n = 130 597)

Prostate(n = 853 030)

Age, mean (SD), y 61.0 (13.3) 68.2 (12.5) 68.4 (9.5) 64.2 (8.2)

Sex

Men 9975 (0.9) 45 690 (49.4) 64 217 (49.2) 853 030 (100)

Women 1 155 610 (99.1) 46 804 (50.6) 66 380 (50.8) 0

Race

White 983 914 (84.4) 78 371 (84.7) 115 707 (88.6) 702 325 (82.3)

Black 123 602 (10.6) 10 105 (10.9) 10 672 (8.2) 114 866 (13.5)

Other 47 839 (4.1) 3311 (3.6) 3428 (2.6) 22 492 (2.6)

Unknown 10 230 (0.9) 707 (0.8) 790 (0.6) 13 347 (1.6)

Charlson-Deyo comorbidityindex

0 972 709 (83.5) 62 598 (67.7) 65 501 (50.2) 714 779 (83.8)

1 154 624 (13.3) 21 251 (23.0) 44 356 (34.0) 116 256 (13.6)

2 29 455 (2.5) 6052 (6.5) 15 434 (11.8) 17 227 (2.0)

≥3 8797 (0.8) 2593 (2.8) 5306 (4.1) 4768 (0.6)

Insurance status

Private 615 151 (52.8) 32 267 (34.9) 35 395 (27.1) 432 141 (50.7)

Medicaid 435 077 (37.3) 53 502 (57.8) 6029 (4.6) 17 371 (2.0)

Medicare 67 379 (5.8) 3215 (3.5) 83 790 (64.2) 364 414 (42.7)

Other government 11 343 (1.0) 673 (0.7) 1508 (1.2) 16 813 (2.0)

Not insured 20 751 (1.8) 1753 (1.9) 2223 (1.7) 11 225 (1.3)

Unknown 15 884 (1.4) 1084 (1.2) 1652 (1.3) 11 066 (1.3)

Income, $a

≥63 000 437 449 (37.5) 30 176 (32.6) 37 973 (29.1) 306 582 (35.9)

48 999-62 999 311 632 (26.7) 24 704 (26.7) 35 532 (27.2) 227 446 (26.7)

38 000-47 999 243 629 (20.9) 21 744 (23.5) 32 398 (24.8) 185 032 (21.7)

vs 7.9%; P < .001); high-risk prostate cancer at TTI 181 to 365 days (11.6% vs. 12.8%; P = .02); andstage I breast cancer (predicted mortality vs TTI 8-60 days [9.7%]: 61-120 days, 11.0%; P = .04;121-180 days, 13.7%; P = 0.01; 181-365 days, 15.2%; P = 0.03). In these subgroups all-cause mortalitywas higher for Black patients compared with White, but the effect size of increased TTI on mortalitywas less pronounced in Black patients. Race-specific predictions for 5-year and 10-year mortality bydisease, stage, and TTI can be found in the eTable in the Supplement.

Discussion

The COVID-19 pandemic has forced many hospitals in the US to grapple with decisions on how bestto optimize allocation of limited health care resources. Postponing particular cancer treatments maylead to disease progression, metastasis, and, ultimately, cancer-related death. Guidelines developedby hospitals, states, and professional societies are largely based on expert opinion and often conflictwith each other.24-27 Relying on the largest hospital-based registry in the US, we found varyingassociations between increased TTI and definitive treatment-eligible cancers, although at least somestages of all 4 of the most common cancers benefitted to some degree from a short TTI.

Table 1. Baseline Clinical Demographic Characteristics of Nonmetastatic Cancer Patients in NCDB Database,2004-2015 (continued)

Characteristics

Patients, No. (%)Breast(n = 1 165 585)

Colon(n = 92 494)

NSC lung(n = 130 597)

Prostate(n = 853 030)

AJCC clinical stagec

0, low risk 52 000 (4.5) NA NA 237 739 (27.9)

I 715 138 (61.4) 52 975 (57.3) 105 266 (80.6) 378 034 (44.3)

II 319 411 (27.4) 24 388 (26.4) 25,31 (19.4) 237 257 (27.8)

III, high risk 79 036 (6.8) 15 131 (16.4) NA NA

Abbreviation: AJCC, American Joint Committee onCancer; NA, not applicable; NCDB, National CancerDatabase; NSC, non-small cell.a Income reflects the median income in the patient’s

zip code.b Educational attainment reflects the number of adults

in the zip code who did not graduate high school,with zip codes ranked in the US by tertile.

c AJCC clinical prognostic group for breast cancer; Riskgroup (D’Amico classification) for prostate cancer(0 = low risk, 1 = intermediate risk, 2 = high risk).

Table 2. Descriptive Statistics by Cancer and Stage for Time-to-Treatment Initiation (TTI), NCDB 2004-2015

Cancer TTI, median (IQR), d

Proportion treated by TTI, %

8-60 d 61-120 d 121-180 d 181-365 dBreast

Stage 0 34 (21-52) 81.6 15.4 2.2 0.8

Stage I 33 (22-48) 85.5 12.9 1.2 0.4

Stage II 33 (22-49) 84.9 12.8 1.5 0.8

Stage III 31 (21-46) 86.3 10.3 2.0 1.4

All stages 32 (21-48) 85.2 12.8 1.4 0.6

Colon

Stage I 28 (18-43) 87.2 10.3 1.7 0.8

Stage II 23 (15-35) 92.9 6.0 0.8 0.3

Stage III 22 (14-34) 93.1 5.7 0.9 0.4

All stages 26 (16-40) 89.7 8.4 1.3 0.6

Non-small cell lung

Stage I 41 (27-62) 73.3 21.6 3.4 1.4

Stage II 41 (27-60) 75.3 20.9 2.9 0.9

All stages 41 (27-62) 74.0 21.5 3.3 1.3

Prostate

Low risk 83 (57-124) 28.0 46.0 16.1 10.0

Intermediate risk 77 (53-112) 32.8 46.0 14.2 7.1

High risk 80 (54-118) 31.8 44.3 16.2 7.7

All risks 79 (55-117) 31.2 45.5 15.3 8.1Abbreviations: IQR, interquartile range; NCDB,National Cancer Database.




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Of the various cancer stages examined, increased TTI was associated with the most negativesurvival effects for stage II and III breast cancer, in keeping with a recent systematic review findingthat surgery should ideally occur less than 90 days from diagnosis and chemotherapy less than 120days from diagnosis, with worse outcomes associated with delays for the disease stages and receptorstatuses studied.28 Current recommendations by the COVID-19 Pandemic Breast Cancer Consortium

Table 3. Predicted Mortality Table for 4 Common Forms of Cancer by Time to Definitive Treatment Initiation and Mortality Endpointa

Cancer

Predicted mortality, 5 y, % Predicted mortality, 10 y, %

TTI 8-60 d TTI 61-120 d TTI 121-180 d TTI 181-365 d TTI 8-60 d TTI 61-120 d TTI 121-180 d TTI 181-365 dBreast

Stage 0 9.6 10.1 12.1 15.3 19.2 20.0 23.6 28.9

Stage I 9.7 11.0 13.7 15.2 20.7 23.0 27.8 30.5

Stage II 17.0 17.7 20.0 21.7 29.4 30.5 34.0 36.5

Stage III 29.6 29.4 32.5 32.7 45.4 45.2 49.2 49.5

Colon

Stage I 22.1 26.6 27.5 29.7 36.3 42.4 43.6 46.5

Stage II 30.2 36.2 43.2 39.7 46.6 54.0 62.1 58.1

Stage III 34.6 38.9 42.1 47.8 48.9 54.0 57.6 63.8

Non-small cell lung

Stage I 43.4 47.4 49.6 47.6 68.3 72.6 74.8 72.8

Stage II 60.8 62.0 60.6 59.6 80.1 81.2 80.0 79.1

Prostate

Low risk 4.9 5.0 5.1 5.2 17.3 17.6 17.9 18.3

Intermediate risk 7.0 7.4 7.9 8.3 19.4 20.4 21.8 22.6

High risk 11.6 12.8 13.8 14.1 28.6 31.2 33.2 33.8

Abbreviation: TTI, time-to-treatment initiation.a Bolded cells contain projections of statistically significantly altered mortality for TTI

when compared with the referent TTI interval of 8 to 60 days. For the cancer stages for

which we identified an interaction between TTI and race, the displayed value is theoverall effect size for all races.

Figure 2. Predicted Probability of Survival of Breast and Non-Small Cell Lung Cancers from Diagnosis to Treatment Initiation

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advocate for neoadjuvant chemotherapy or endocrine therapy in patients who cannot undergoupfront surgery because of limited surgical capacity, although use of neoadjuvant systemic therapyin some of these populations (eg, ER-positive DCIS and T1N0 ER-positive cancers) remainsunsubstantiated by high-level prospective data,29 with similar recommendations from the Society ofSurgical Oncologists.4,16 The exception remains for patients with ER-negative DCIS, for whom nosystemic treatment option exists. Our results showed significant differences in all-cause mortalitywith delayed definitive therapy even for stage I patients, although the effect size is clinically small.Patients with stage IA or IB breast cancer who were not treated until 61 to 120 days after diagnosishad 1.3% and 2.3% increased mortality at 5 years and 10 years, respectively, and those waiting longersuffered even greater increases in mortality. As such, our analysis underscores the importance oftimely definitive treatment, even for stage I breast cancer.

The recommendations from both the American College of Surgeons and the Society of SurgicalOncologists for treatment of colon cancer during the COVID-19 pandemic are to continue to operateon known malignant masses, deferring treatment only for malignant polyps or sub–2 cm lungcancers.4,16 This urgency could be because colon cancer is subject to particularly long diagnosticintervals between first presentation for evaluation and date of diagnosis, which increases the totallength of time between incidence of cancer and treatment.30 For colon cancer, we observed thateach additional 60-day delay was associated with a 0.9% to 4.6% increase in 5-year all-causemortality for stage I cancers, and a 3.2% to 6.0% increase in 5-year mortality for stage III cancers,with a longer 10-year time horizon resulting in larger effect sizes for increasing TTI. While ouranalyses may conflict with a systematic review finding no association with increased TTI on overallsurvival for colon cancer, this is partially because of differing methodology, as their longest delaycategory was greater than 55 days.31

For stage I lung cancer, we observed 4.0% to 6.2% absolute increases in 5-year mortality forincreased TTI groups compared with the 8 to 60–day reference group, with larger effect sizes on10-year mortality. The Kaplan-Meier survival curves for various levels of TTI for stage IIA/B cross at 2separate time points, so we were unable to make conclusions about stage II lung cancer. The

Figure 3. Predicted Probability of Survival of Colon and Prostate Cancers from Diagnosis to Treatment Initiation

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association between TTI and survival has previously been studied with conflicting results.32 Nadparaet al33 analyzed 16 747 patients in SEER and found a paradoxical association of improved survivalwith greater TTI, replicating prior work.34 Conversely, other studies have found better outcomes fortimely treatment both in stage IA disease35 and in all localized disease.36 The COVID-19–related ACSrecommendation is to treat all stage I and II patients except those with sub–2 cm masses.16

Meanwhile, the NCCN recommends deferral of stage IA1 tumors for 2 to 3 months, with urgentsurgery within 1 month reserved for Stage IA2 through IIB tumors.37 Our analysis of increasedtreatment initiation in lung cancers therefore supports the current American College of Surgeonsrecommendations, but lack the granularity necessary to evaluate differentiating between stages IA1and IA2-IIB per the NCCN guidelines.

As might be expected, increased TTI for prostate cancer was associated with lower mortalityrates than for the other cancers examined. However, our findings for high-risk prostate cancer are ofparticular interest. Most prior work has found no association between clinical outcomes and delaysin definitive therapy for localized prostate cancer, even with TTI of up to 6 months for high-riskprostate cancer.38,39 Based on these data, the NCCN recommended that treatment for low-risk andfavorable intermediate-risk prostate cancer can be avoided during the COVID-19 pandemic, andunfavorable intermediate-risk and high-risk disease can safely be deferred for “upward of 6months,”24 while other groups have recommended continued treatment of intermediate-risk andhigh-risk prostate cancer.25-27 By including low-risk prostate cancer patients in our analysis, weincluded a group that is widely considered safe to monitor and who should have a minimal andnonsignificant increase in mortality with treatment delay in the absence of upstaging,20,39 whichindeed is what was observed. We found all-cause mortality differences of 2.2% at 5 years and 4.6%at 10 years between high-risk patients who were treated expeditiously vs those waiting 4 to 6months (inside the current NCCN allowable deferral period), and differences of 0.9% at 5 years and2.4% at 10 years for similar intermediate-risk patients. Our findings suggest that there is a limit to thelength of treatment deferral that provides acceptable outcomes, and will be of use for urologists bothin pandemic settings and otherwise.

Our study has important policy implications for the current pandemic, for triage of cancer care inresource-limited settings, and for future crises, as health care may be affected by future natural disas-ters, pandemics, and supply chain constraints. Our analyses suggest a rank order for prioritizing whichpatient cases could still be performed in resource-limited settings and the order in which cases shouldbe added back to the treatment schedule as resource limitations ease. Our initial analysis of these com-mon cancers provides foundational evidence on these discussions. Our study also found worse mortal-ity for Black patients across cancers, but we found an inconsistent signal that increased TTI may have aweaker association with mortality for Black patients, potentially because of higher baseline risk.

LimitationsOur study has several limitations. The main limitation is that drivers of increased TTIs in our patientcohort may differ from those in a pandemic. Patients in our cohort may have confounding factorswhich are linked to both worse outcomes and TTI, including low health literacy, poor access to care,and care at lower-quality hospitals, which could limit the generalizability of our findings.9-11,19,22 Allpatients are exposed to resource limitations in pandemic conditions, including those who areunaffected by these confounders, though disparities in care persist for racial minority groups.40

Therefore, our analysis can be thought of as a “worst case scenario” in estimating the effects of hightimes between diagnosis and treatment. We believe bias in this direction to be preferable, however,as it is more useful for hospital administrators, clinicians, and policymakers to know the upper limiteffect size for predicted mortality potentially associated with triage decisions, especially whencompared with underestimation owing to best-case biased analyses. We also note that in a pandemicspecifically there are important other competing risks to consider, and the nuanced decision ofwhether the benefit of cancer treatment outweighs the risk of potentially lethal infection depends onfactors outside the scope of our study such as comorbidities and local prevalence patterns.




We acknowledge that our mortality figures for NSCLC and colon cancer are higher than may beexpected.41 However, we did include margin-positive patients by limiting our analysis to variablesthat can be determined during a triage process (margin status must be assessed postoperatively). Wealso report common NCDB-related limitations, including an inability to evaluate nonincludedoutcomes (ie, cancer-specific survival) or to evaluate delayed diagnosis (because NCDB-inclusionrequires cancer diagnosis). We cannot separate patients managed with watchful waiting who weretreated after developing symptoms from those who delayed definitive therapy. We acknowledgethat because of our convenience sample it is possible that nonsignificant findings were the result ofa lack of power, although our samples were large. Finally, our cohort was limited to patients treated atfacilities reporting to the NCDB, which may not accurately reflect national practice patterns, althoughmore than 70% of cancer diagnoses are captured.18

Conclusions

Examining delayed curative-intent treatment for breast, lung, colon, and prostate cancer, we foundthat all benefitted to some degree from a short interval between diagnosis and therapy. Some of ourfindings differ from current guideline recommendations. Specifically, our data support only limiteddeferral for prostate cancer, with length of deferral dependent on risk stratification. Future analyseswill expand to other cancers, which may assist with treatment deferral decisions in resource-limited settings and provide a framework for prioritizing treatments as limitations ease.

ARTICLE INFORMATIONAccepted for Publication: October 25, 2020.

Published: December 14, 2020. doi:10.1001/jamanetworkopen.2020.30072

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Cone EB et al.JAMA Network Open.

Corresponding Author: Eugene B. Cone, MD, Combined Harvard Program in Urologic Oncology at MassachusettsGeneral Hospital, Brigham and Women’s Hospital, 45 Francis St, ASB II-2, Boston, MA 02115 ([email protected]).

Author Affiliations: Division of Urological Surgery, Brigham and Women’s Hospital, Boston, Massachusetts (Cone,Marchese, Paciotti, Nguyen, Nabi, Cole, Kibel, Trinh); Center for Surgery and Public Health, Brigham and Women’sHospital, Boston, Massachusetts (Cone, Marchese, Nguyen, Nabi, Cole, Trinh); Department of Urology, HumanitasClinical and Research Center IRCCS, Rozzano, Italy (Paciotti); Division of Surgical Oncology, Brigham and Women’sHospital, Boston, Massachusetts (G. Molina); Department of Obstetrics and Gynecology, Beth Israel DeaconessMedical Center, Boston, Massachusetts (R. L. Molina); Division of Breast Surgery, Brigham and Women’s Hospital,Boston, Massachusetts (Minami); Department of Epidemiology, Harvard T.H. Chan School of Public Health,Boston, Massachusetts (Mucci).

Author Contributions: Drs Cone and Trinh had full access to all of the data in the study and take responsibility forthe integrity of the data and the accuracy of the data analysis.

Concept and design: Cone, Marchese, Nabi, Cole, Mucci, Kibel, Trinh.

Acquisition, analysis, or interpretation of data: Cone, Marchese, Paciotti, Nguyen, Nabi, G. Molina, R. Molina,Minami, Kibel, Trinh.

Drafting of the manuscript: Cone, Marchese, Paciotti, Nguyen, Minami, Kibel, Trinh.

Critical revision of the manuscript for important intellectual content: Cone, Marchese, Nguyen, Nabi, Cole, G.Molina, R. Molina, Minami, Mucci, Kibel, Trinh.

Statistical analysis: Marchese, Paciotti, Nguyen.

Obtained funding: Cole, Kibel.

Administrative, technical, or material support: Cone, Nabi, Kibel.

Supervision: Cone, Mucci, Kibel, Trinh.




https://jama.jamanetwork.com/article.aspx?doi=10.1001/jamanetworkopen.2020.30072&utm_campaign=articlePDF%26utm_medium=articlePDFlink%26utm_source=articlePDF%26utm_content=jamanetworkopen.2020.30072https://jamanetwork.com/journals/jamanetworkopen/pages/instructions-for-authors#SecOpenAccess/?utm_campaign=articlePDF%26utm_medium=articlePDFlink%26utm_source=articlePDF%26utm_content=jamanetworkopen.2020.30072mailto:[email protected]:[email protected]

Conflict of Interest Disclosures: Dr Kibel reported receiving personal fees from Bayer, Janssen Pharmaceuticals,Pfizer, Merck & Co, Bristol Myers Squibb, Advantagene Inc, Insightec, and Profound outside the submitted work;he also receives research support from the DiNovi Family Foundation. Dr Mucci reported receiving researchfunding from Bayer, Astellas Pharma, Sanofi, Janssen Pharmaceuticals, and AstraZeneca. Drs Trinh and Mucci areProstate Cancer Foundation Young Investigators. Dr Trinh reported receiving research support from a HealthServices Research pilot test grant from the Defense Health Agency and an unrestricted educational grant from theVattikutti Urology Institute; he also reported receiving personal fees from Astellas Pharma, Bayer, JanssenPharmaceuticals, Insightec, and Intuitive Surgical outside the submitted work. No other disclosures were reported.

Disclaimer: The American College of Surgeons and the Commission on Cancer have not verified and are notresponsible for the analytic or statistical methodology employed or the conclusions drawn from these data by theinvestigator.

Meeting Presentations: This work won first prize in the Commission on Cancer 2020 Cancer Research PaperCompetition and was virtually presented at the Commission on Cancer Plenary Session; October 30, 2020.

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SUPPLEMENT.eAppendix 1. Selection Criteria by Cancer CohorteAppendix 2. Definitions of Definitive Therapy by CancereTable. Predicted Mortality Table by Time-to-Definitive-Treatment Initiation (TTI), Mortality Endpoint, Cancer,Stage, and Race



https://dx.doi.org/10.1016/j.eururo.2013.02.024https://dx.doi.org/10.15585/mmwr.mm6933e1https://dx.doi.org/10.15585/mmwr.mm6933e1https://dx.doi.org/10.6004/jnccn.2014.0099

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