Cancer Mobile Screening Units for the Early Detection ... · Review Mobile Screening Units for the Early Detection of Cancer: A Systematic Review Zo€e R. Greenwald 1,2, Mariam El-Zein2,

Review

Mobile Screening Units for the Early Detectionof Cancer: A Systematic ReviewZo€e R. Greenwald1,2, Mariam El-Zein2, Sheila Bouten2, Heydar Ensha2,Fabiana L. Vazquez3, and Eduardo L. Franco1,2

Abstract

Mobile screening units (MSUs) provide cancer screening ser-vices outside of fixed clinical sites, thereby increasing access toearly detection services. We conducted a systematic review of theperformance of MSUs for the early detection of cancer. Databases(MEDLINE, EMBASE, Cochrane Library, WHO Global HealthLibrary, Web of Science, PsycINFO) were searched up to July2015. Studies describing screening for breast, cervical, and coloncancer using MSUs were included. Data were collected foroperational aspects including the performance of exams, screen-ing tests used, and outcomes of case detection. Of 268 identifiedstudies, 78 were included. Studies investigated screeningfor cancers including breast (n ¼ 55), cervical (n ¼ 12), colon

(n ¼ 1), and multiphasic screening for multiple cancers (n ¼ 10).The median number of screening exams performed per interven-tion was 1,767 (interquartile range 5,656–38,233). Programsoperated in 20 countries, mostly in North America (36%)and Europe (36%); 52% served mixed rural/urban regions, while35% and 13% served rural or urban regions, respectfully.We conclude that MSUs have served to expand access to screeningin diverse contexts. However, further research on the implemen-tation of MSUs in low-resource settings and health economicresearch on cost-effectiveness of MSUs compared with fixedclinics to inform policymakers is needed. Cancer Epidemiol BiomarkersPrev; 26(12); 1679–94. �2017 AACR.

IntroductionThe implementation of screening and early detection programs

is a cornerstone of cancer prevention (1, 2). Despite evidence thatearly detection saves lives, global disparities in access to servicespersist (1). Barriers to cancer screening include lack of provideravailability, community access to screening and communitydemand for screening (3). Challenges related to health careproviders can include shortages in screening delivery or policiesthat require a referral from a family physician to access screening.Community access to screening can be limited by prohibitivecosts or inaccessibility of screening clinics due to distance, hoursof operation, or a lack of knowledge about where to go forscreening. Finally, client demand for screening can pose as abarrier in situations where individuals are unaware of the benefitsof screening, do not perceive themselves at risk, or fear screeningresults.

Mobile screening units (MSUs) are an innovative alternative toscreening exams in clinics or hospitals and may include vans,recreational vehicles, or other traveling clinics that are staffed by

health workers and outfitted with equipment for early detection.MSUs allow care providers to increase their capacity for servicedelivery outside of fixed clinics, which is particularly important inareas without an infrastructure for cancer screening services (4).MSUs increase community access by offering screening in con-venient locations thus decreasing the distance and travel timeneeded to access screening services (5). MSUs also present uniquechallenges for service delivery, such as more complicated referralsystems as individuals with abnormal exams commonly need toreport to a specialty clinic for follow-up.

Previous narrative literature reviews of community-basedscreening initiatives have concluded that eliminating struct-ural barriers such as location, distance, and inconvenienthours of operation is highly effective in increasing screeningin high-income countries (3, 5). In 1995, a National CancerInstitute survey of 1,057 mammogram facilities in the UnitedStates showed that 2.4% of screening services were offered inMSUs, which demonstrated similar quality indicators as fixedclinics with respect to certification of personnel, quality con-trol practices, and frequency of equipment verification bymedical physicists. In addition, the NCI survey found MSUsbenefitted clients by offering lower fees, accessible eveningoperating hours, and serving a higher proportion of self-referred women (4). A survey on barriers to breast and cervicalcancer screening among underserved populations in the Unit-ed States found MSUs to be an effective strategy for reachingwomen over the age of 60 years, some of whommay be unableto travel to fixed clinics (6). Overall, current evidence tosupport the operations of MSU programs is limited, withsummaries available only through dated reviews (6–8) andinformal medical forums (9). In addition, none of the priorreviews included data on performance measures, such as recallrates and case detection rates.

1Department of Epidemiology, Biostatistics and Occupational Health, McGillUniversity, Montr�eal, Qu�ebec, Canada. 2Department of Oncology, McGill Uni-versity, Montr�eal, Qu�ebec, Canada. 3Department of Teaching and Research,Barretos Cancer Hospital, Barretos, S~ao Paulo, Brazil.

Note: Supplementary data for this article are available at Cancer Epidemiology,Biomarkers & Prevention Online (http://cebp.aacrjournals.org/).

Corresponding Author: Zo€e R. Greenwald, Department of Oncology, McGillUniversity, 5100 Maisonneuve BlvdWest, Suite 720; Montr�eal, Quebec H4A 3T2,Canada. Phone: 416-880-0965; Fax: 514-398-5002; E-mail:[email protected]

doi: 10.1158/1055-9965.EPI-17-0454

�2017 American Association for Cancer Research.

CancerEpidemiology,Biomarkers& Prevention

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To our knowledge, no systematic review has synthesized resultson the implementation of MSU programs. This systematic reviewsummarizes the evidence from qualitative, quantitative, andmixed-method studies on the implementation of MSUs for earlycancer detection worldwide.

Materials and MethodsInclusion criteria

We adhered to the PRISMA guidelines and followed a reviewprotocol (10). Empirical studies that included a description ofcancer screening for breast, cervical, and colorectal cancer takingplace on MSUs were eligible for inclusion. No restrictions wereplaced on study design, study location, and participants. Studiesreporting on screening tests to detect precancerous lesions or earlyinvasive cancer were eligible. Both organized and opportunisticscreening programs were included. Only studies published inEnglish, French, or Portuguese were considered. Studies wereexcluded if data on theMSUprogramwere not reported separatelyfrom those of a fixed clinic.

The following databases were searched through to July 2015:EMBASE (via Ovid), MEDLINE and PubMed (via Ovid),Cochrane Library, WHO Global Health Library, Science CitationIndex Expanded (via Web of Science), Social Sciences CitationIndex (via Web of Science), and PsycINFO (via Ovid). Additionalstudieswere identified through bibliographies of included studiesand consulting subject matter experts. The search strategy wasdeveloped by a medical librarian and used the following searchterms to query databases: mobile, movable, traveling, unit, clinic,facility, hospital, early detection, neoplasms, cancer screening,cancer prevention, and cancer diagnosis. A full search strategy isincluded in Supplementary Table S1. Only published articles inpeer-reviewed journals or thesis dissertations were included.Conference abstracts/posters, review articles, and opinion pieceswere excluded.

Study selection and data collection processWe first reviewed titles and abstracts of potentially relevant

citations. The full text of eligible articles was then screened byone author and verified by a second. Disagreements betweenauthors were resolved by discussion or consultation with athird author. Reasons for the exclusion of full-text articles wererecorded.

Two authors then independently reviewed full-text articles.Data were extracted onto a piloted comprehensive and standard-ized data abstraction sheet by one author and validated by asecond author. The following information was extracted: studydesign, country, cancer site(s), screening test(s), size of targetpopulation, number of screening exams and/or number of indi-viduals screened, participant sociodemographic characteristics,type of MSU, operational characteristics of MSU (with respect tothe number of screening tests offered, daily kilometer distancetraveled, locations of follow-up facilities, etc.) and performancemeasures of screening including the rate of abnormal calls, biopsyrate, losses to follow-up, timeliness of follow-up, number ofdetected cases, and characteristics of detected cases includingstaging and extent of disease. Test validity measures includingsensitivity, specificity, positive predictive value, and negativepredictive value were extracted when reported or otherwise man-ually calculated (formulas provided in Supplementary Table S2).We considered screening programs to be organized if they were

part of a systematic program where every individual in a targetpopulation was invited to attend screening.

We collected economic data when reported; however, noanalyses were conducted due to the broad time range of includedstudies and nontransferability of costs of medical equipment andinfrastructure from past to present. If key data were missing fromstudies, we contacted the investigators of original studies pub-lished within the last 10 years to obtain the information. Wheremultiple reports of the same study were published, we extracteddata from the most recent or comprehensive publication.

The risk of bias for a subset of individual studies reportingdetected cancer caseswas independently appraisedby twoauthorsusing the Mixed Methods Appraisal Tool (MMAT; ref. 11) pro-vided in Supplementary Table S3. This tool was selected for itscapacity to appraise quantitative, qualitative, and mixed-methodstudies. The content validity and reliability of the MMAT forjudging methodologic quality has been previously validated(12). We rated each study according to four criteria via a scoreranging from 100% (all criteria met) to 0% (no criteria met).MMAT methodologic criteria indicators vary by study design toassess systematic error such as sampling, selection, confounding,and information biases. Conflicts were resolved by consensus orconsultation with a third author. Wemodified the tool to includea criterion to assess the methodologic quality of screening pro-grams for studies using a quantitative descriptive design withoutcomparison group. The modified criterion assessed whether therate of follow-up among abnormal screening exams was above80%. We used an 80% threshold as this has been previouslyestablished by WHO early detection programme guidelines as aminimum acceptable rate of follow-up (2). In addition, wehypothesized that loss to follow-up among abnormal screeningexams would introduce information bias into studies, leading toan underestimation of case detection rates.

Summary measuresBecause of the heterogeneity in study endpoints and the pres-

ence of noncomparative study designs, the studies were notamenable to statistical analyses and no meta-analysis was possi-ble. Studies were thus summarized qualitatively in terms of keystudy characteristics, such as the number of screening examsperformed on MSUs, and duration of program operations, andperformance outcomes including the rate of abnormal calls,biopsy rate, number of detected cases, and characteristics ofdetected cases, without an overall summary effect measure. Out-comes were graphically displayed for continuous data, such as theperformance of programs in terms of case detection rates per1,000 screening exams.

The implementation of the MSU programs are described withrespect to three evidence-based factors associated with successfuldelivery of population-based screening services: provider delivery,community access, and community demand (3). We also sum-marized available information on the referral systems of MSUprograms and reported rates of loss to follow-up followingabnormal exams.

ResultsThe initial search yielded 441 articles. An additional 27 records

were identified through other sources. After checking for dupli-cates, there were 268 unique hits. Careful analysis of titles andabstracts resulted in 140 eligible articles. Of these, 78 studies met

Greenwald et al.

Cancer Epidemiol Biomarkers Prev; 26(12) December 2017 Cancer Epidemiology, Biomarkers & Prevention1680



the inclusion criteria and were included in the review (Fig. 1;Table 1). Twelve studies were excluded due to screening for sitesof cancer for which current evidence does not support efficacy ofscreening among the general population, such as for skin cancer(n ¼ 5), lung cancer (n ¼ 3), gastric cancer (n ¼ 2), oral cancer(n ¼ 1) and prostate cancer (n ¼ 1). Key operational aspects ofthese MSU studies are summarized in Supplementary Table S4.

Study characteristicsThe majority of MSU interventions (n ¼ 55) targeted breast

cancer while other studies involved cervical cancer (n ¼ 12),colon cancer (n ¼ 1), or multiphasic screening for multiplecancer sites (n ¼ 10). A summary of operational measures by

site of cancer screening is presented in Table 2. Studies werepublished between 1970 and 2016 and were conducted in 20countries, with the majority from Europe (36%), North Amer-ica (36%), Latin America (13%), and Asia (11%); 52% of MSUsoffered services in both rural and urban areas, while 35% ofprograms exclusively served rural regions and 13% exclusivelyurban areas. Overall, 28% of studies were part of organizedscreening programs.

Study designs, based on the classifications for mixed studydesigns (11), are reported in Table 1. The majority were of aquantitative descriptive nature (64% including 50 single-groupstudies of cancer incidence/prevalence or operational measuresand three studies of cost-effectiveness); a further 22% were

Figure 1.

PRISMA flow diagram of studies for inclusion.

Mobile Screening Units for the Early Detection of Cancer

www.aacrjournals.org Cancer Epidemiol Biomarkers Prev; 26(12) December 2017 1681



Table 1. Line listing of included studies by cancer site

Site ofcancer

Study authors,publication year Country Screening test

Studylengthyears

Numberof MSUexams

Study designa

case detectionreported

Breast cancer Reuben, 2002 (37) USA Mammogram (NOS) 2 129 RCTRimer, 1992 (59) USA Mammogram (NOS) — — RCTWilliams, 1989 (77) UK Mammogram (NOS) — 316 RCTTabar, 1981 (22) Sweden Film mammogram 2.3 34,187 RCTa

Strax, 1973 (23) USA Film mammogram, CBE 5 20,211 RCTa

Hughes, 2014 (13) Australia Film mammogram 9 214,328 Prospective cohorta

Mizuguchi, 2014 (53) USA Digital, film mammogram 10 48,324 Prospective cohorta

Horton, 1996 (66) UK Film mammogram 0.5 4,578 Prospective cohortRoen, 2013 (33) USA Digital mammogram 2 1,771 Retrospective cohortDel Turco, 2007 (18) Italy Digital, film mammogram 1.8 28,770 Retrospective cohorta

Zappa, 2002 (76) Italy Film mammogram 9 80,134 Retrospective cohorta

Fayanju, 2014 (34) USA Mammogram (NOS) 5 7,334 Cross-sectionalFontenoy, 2013 (14) Canada Digital, film mammogram 8 42,279 Cross-sectionala

Van Hal, 1999 (78) Belgium Mammogram (NOS) 0.2 — Cross-sectionalStark, 1997 (28) UK Mammogram (NOS) — — Cross-sectionalOrton, 1991 (46) UK Mammogram (NOS) 1 1,408 Cross-sectionalS�eguret, 1995 (72) France Film mammogram 2.5 26,026 Cross-sectionala

Roberson, 1994 (63) USA CBE — 271 Cross-sectionalAl Mulhim, 2015 (69) Saudi Arabia Digital mammogram 5 8,061 DescriptiveApffelstaedt, 2014 (31) South Africa Digital mammogram 1.5 2,712 Descriptivea

Renck, 2014 (16) Brazil Mammogram (NOS) — 9,919 Descriptivea

Brooks, 2013 (42) USA Digital mammogram, CBE 2 4,543 Descriptivea

Carkaci, 2013 (17) USA Digital, film mammogram 20 6,776 Descriptivea

Haikel, 2013 (30) Brazil Film mammogram 2 10,521 Descriptivea

Lee, 2013 (79) Taiwan Mammogram (NOS) 0.3 — DescriptiveVyas, 2013 (44) USA Digital mammogram 2 1,161 DescriptiveBond, 2009 (41) UK Mammogram (NOS) 3 39,260 DescriptiveRodriguez-Cuevas, 2009 (71) Mexico Film mammogram 1.5 96,828 Descriptivea

Copeland, 2008 (45) USA Mammogram (NOS) 1 3,336 DescriptivePeek, 2007 (43) USA Mammogram (NOS) 1.5 — DescriptiveMaheswaran, 2006 (39) UK Mammogram (NOS) 3 16,695 DescriptiveLane, 2003 (51) USA Mammogram (NOS) — 141 DescriptiveTinkler, 2001 (80) UK Mammogram (NOS) 0.7 — DescriptiveGordenne, 2000 (78) Belgium Mammogram (NOS) 8 52,475 Descriptivea

Frelix, 1999 (35) USA Film mammogram, CBE 1.1 1,935 Descriptivea

Swaddiwudhipong, 1999 (81) Thailand CBE 1 — Descriptivea

Kann, 1998 (82) USA Film mammogram, CBE 5 19,280 Descriptivea

Schweitzer, 1998 (83) USA Film mammogram 3 10,859 DescriptiveFalshaw, 1996 (32) UK Mammogram (NOS) — 338 DescriptiveKohli, 1995 (40) UK Mammogram (NOS) 1 11,425 DescriptiveSutton, 1995 (65) UK Mammogram (NOS) 0.3 306 DescriptiveVan Oyen, 1994 (74) Belgium Mammogram (NOS) 3 16,017 Descriptivea

Garas, 1994 (73) Greece Film mammogram — 22,258 Descriptivea

McCoy, 1992 (36) USA Film mammogram 4.3 16,354 Descriptivea

Dershaw, 1992 (55) USA Film mammogram 3 22,540 Descriptivea

Kessler, 1991 (56) USA Film mammogram 1.1 3,627 DescriptiveWilliams, 1990 (84) UK Film mammogram 4 6,409 DescriptiveRubin, 1990 (85) USA Film mammogram 0.5 2,099 DescriptiveHaiart, 1990 (68) UK Film mammogram 0.5 6,080 DescriptiveKettlehake, 1988 (57) USA Film mammogram 0.9 5,000 DescriptiveHamilton, 2003 (62) UK Mammogram (NOS) — — Qual. descriptiveScammon, 1991 (38) USA Mammogram (NOS) — — Qual. descriptiveKennedy, 2009 (60) USA Mammogram (NOS) 2 — Case studyNielsen, 1991 (86) USA Mammogram (NOS), CBE — �8,000 Case studyKluhsman, 2009 (52) USA Film mammogram 18 4,606 Descriptive

Cervical cancer Fregnani, 2013 (27) Brazil Pap, Pap-LBC 0.6 12,048 Cross-sectionala

Megevand, 1996 (15) South Africa Pap, VIA 0.7 5,045 Prospective cohorta

Lorenzi, 2016 (21) Brazil HPV testing, Pap-LBC 0.8 3,068 Descriptivea

Ferris, 2015 (26) Peru Pap 2 1,700 DescriptiveCheng, 2014 (87) Taiwan Pap 5 85 DescriptivePaengchit, 2014 (25) Thailand HPV testing, Pap-LBC 0.3 2,000 Descriptivea

Riza, 2000 (88) Greece Pap 9 19,961 DescriptiveSwaddiwudhipong, 1999 (20) Thailand Pap 4 — Mixed-methods: Descriptivea

Thornton, 1989 (54) UK Pap, CBE 0.5 568 Descriptivea

Brindle, 1976 (49) UK Pap 0.1 1,526 Descriptivea

(Continued on the following page)

Greenwald et al.




nonrandomized quantitative studies (including three prospectiveand four retrospective cohort studies, and 10 cross-sectionalstudies comparing outcomes between two groups); 6% wererandomized control trials (RCT; n ¼ 5) and 8% (n ¼ 6) werequalitative descriptive or case studies.

As shown in Table 3, 32 studies reported performance mea-sures. The quantitative descriptive studies (n ¼ 22) measuredvarious implementation, clinical and service-related outcomes,and generally explicitly or implicitly stated the objective of eval-uating the performance of the MSU program. The nonrando-mized observational studies (n ¼ 7) sought to answer morespecific questions, often with respect to comparisons in screeningmodalities such as the effectiveness of MSU as compared withfixed clinic screening (13–16); breast cancer studies comparingdigital to film-screen mammography (17, 18); cervical cancerstudies comparing conventional Pap cytology with liquid-basedPap cytology (Pap-LBC) tests (19, 20) or human papillomavirus(HPV) testing with Pap-LBC (21). Two RCTs for mammographyscreening sought to establish evidence of mortality reductionsassociated with screening (22, 23).

Quality reviewThe mean overall score was 74.2% for the 29 studies assessed

for methodologic quality (Table 3), indicating a fair level ofmethodologic quality across studies. Trends in the risk of biasby study design are presented in Fig. 2. The overall quality scorewas 72% for the 22 descriptive studies (Fig. 2A) and 82% for thesevennonrandomized observational studies (Fig. 2B). A commonweaknesswas incompleteness in reporting outcomes,with50%ofthe descriptive studies and 29%of nonrandomized observationalstudies providing no information on follow-up rates. Two RCTsfor breast cancer received scores of 100% (22) and 50% (23).

Screening tests by cancer siteFifty-five studies described breast cancer screening using a range

of tests including digital or analog film-screen mammographyand clinical breast exams. In addition, all 10 multiphasic pro-grams offered breast screening. The number of mammographyscreening exams reported per study ranged from 141 to 214,327,and study duration ranged up to 20 years; this indicates theflexibility of MSUs to be used at various capacities in different

Table 1. Line listing of included studies by cancer site (Cont'd )

Site ofcancer

Study authors,publication year Country Screening test

Studylengthyears

Numberof MSUexams

Study designa

case detectionreported

Whitfield, 1972 (50) UK Pap 3 1,952 Descriptivea

Logan, 2011 (61) Ireland Pap — — Case studyColon Bruwer, 2013 (29) South Africa Colonoscopy 2 — Case studyMultiple sites Schnippel, 2015 (89) South Africa Breast and cervical cancer: CBE, Pap

and VIA1 1,756 Cost-effectiveness

Mauad, 2009 (70) Brazil Breast and cervical cancer: Filmmammogram, Pap

1 7,192, 2,964 Descriptivea

Alexy, 1998 (90) USA Breast, Cervical: CBE, Pap — — DescriptiveCraddock, 1975 (91) UK Breast, cervical: Mammogram (NOS),

Pap— — Descriptive

Seacome, 1971 (92) UK Breast, Cervical: CBE, Pap 0.5 — DescriptiveWhitfield, 1970 (93) UK Breast, Cervical: CBE, Pap 0.2 1,064 DescriptiveKumar, 2011 (24) India Breast, cervical and oral: CBE,

VIA/VILI, OVE0.3 182 Descriptive

Yoon, 2009 (64) Korea Breast, cervical, gastric, liver, colon:MMG þ CBE, Pap, upper GI series/endoscopy, serum alpha fetoproteintests and abdominal ultrasonography,FOBT

0.3 — Cross-sectional

Lynch, 1976 (94) USA Breast, cervical, prostate, gastric, oral,lung, colon: Tests unspecified

4 5,232 total Descriptivea

Lynch, 1973 (67) USA Breast, cervical, prostate, gastric, oral,lung, CRC, penile: Mammogram(NOS), CBE, Pap, DVI, OVE, indirectlaryngoscopy, proctosigmoidoscopy

1 — Descriptivea

Abbreviations: CBE, Clinical breast exam; DVI, Direct visual inspection; Pap, Papanicolau smear with conventional cytology; Pap-LBC, Papanicolau smear with liquidbased cytology; NOS, not otherwise specified; OVE, oral visual examination; VILI, visual inspection with Lugol iodine.aStudies report results for number of detected cases of cancer and/or test performance.

Table 2. Overall operational characteristics of included studies by cancer site

Site ofcancer

Numberofstudies

Number screening examsper program: mean(min, max)

Region of operations(% rural, urban, mixed)

Percent organizedscreening, % (n)

Breast 55 21,223 (141–214,328) 24% rural/20% urban/56% mixed 40% (19)Cervical 12 4,954 (85–19,961) 46% rural/54% both 17% (2)Colon 1 — 100% rural 0%Multiphasic 10 1,994 (182–5,232) 18% rural/9% urban/64% mix 18% (2)Total 78 14,069 (85–214,328) 29% rural/10% urban/57% mix 28% (22)





Table

3.Descriptive

summaryofqua

lity,

perform

ance

indicators,a

ndcase

detectionrates

Autho

r,ye

ar,

coun

try,

Stud

ydesign

MMAT

qua

lityscore

Descriptionofinterven

tion

(studyobjective,

target

population,

screen

ingtest,MSU

type,

timeperiodof

stud

y)

Sample

(num

ber

ofclients

screen

edorex

ams,

dem

ographics)

Rep

orted

canc

erscreen

ingperform

ance

indicators

Can

cer

detec

tion

rate/1,000

exam

s

Breast

cancer

AlM

ulhim

etal.

(2015),

Sau

diA

rabia

(69)

Qua

ntitativedescriptive

MMAT:50

%

Target:5

3,800women

�ag

e40sampled

from

15primarycare

centersin

Eastern

Sau

diArabia

Test:digital

MMG;M

SUtype:

2vans

Period:2009–2014

(5ye

ars);opportun

istic

screen

8,061clientsscreen

ed;

mea

nag

e(SD):46.5(9.4);

agerang

e:37

–78

Abno

rmal

callrate:7.9%

(n¼

636

);biopsy

rate:0.7%

(n¼

63)

Detectedcases:n¼

47;

test

PPV¼7

.3%a;

biopsy

PPV¼7

4.6%a

ProportionDCIS:15%

,70.2%

ofcases<2

cm

5.9(firstroun

d);

4.1(later

roun

ds)

Apffelstae

dt

etal.(20

14),

SouthAfrica

(31)

Qua


MMAT:50

%

Target:women

�ag

e40served

by

primaryhe

alth

centersin

Cap

etown

Test:digital

MMG;M

SUtype:

1van

Period:20

11–2012

(2ye

ars);o

pportun

istic

screen

2,712clientsscreen

edAbno

rmal

callrate:9.6%

(n¼

261);b

iopsy

rate:1.2

%(n

¼32

)Lo

stto

follo

w-upam

ong

recalls:4

%(n

¼11)

Detectedcases:n¼

10(5

DCIS,2

stag

eII;

3stag

eIII)

TestPPV¼

3.8%a;b

iopsy

PPV¼3

1%a

3.7

Hug

heset

al.

(2014),

Australia

(13)

Retrospective

coho

rt

MMAT:75

%

Objective:

toco

mparediagno

stic

effectiven

essofMSU-M

MGþ

step

-down

MSUassessmen

tve

rsus

fixed-cen

ter(FC)-

MMGþ

diagno

stic

follo

w-up

Target:women

ages

40–6

9in

Western

Australia

Test:MSU-M

MGþ

"stepdown"

follo

w-upofdiagno

sticview

sin

MSUwith

referral

tourban

FCifbiopsy

isrequired;

MSUtype:

1va

nComparison:

FC-M

MGþ

FCdiagno

stic

follo

w-up

Period:1999–2008(10ye

ars);o

rgan

ized

program

MSU,F

Cgroup

:nu

mber

ofexam

s214,328

,54

5,699

Results

reported

forMSU,F

C:scree

ning

uptake

rate:5

9%,5

7%;rep

eatparticipation

rates(w

ithin27

mos.):64.9%

(64.7–6

5.1),

68.3%

(68.2–6

8.4)

Tum

orsize:17.1mm,17.4mm

Interval

cancer

ratesper

10,000women

:�1

2months:0

.16(0.02–

0.34),0.70

(0.46–0

.94)

13–24months:0

.54(0.18

–0.89),0.76

(0.49–1.03)

Sen

sitivity

¼95%

,91%

3.1(2.8–3

.3)

MSUgroup

vs.

7.04(6.82–

7.27

)FCgroup

Ren

cket

al.

(2014),

Brazil(16)

Cross-sectiona

lan

alytic

MMAT:75

%

Target:W

omen

�ag

e40insouthe

rnBrazil

Test:MSU-M

MG;MSUtype:

1va

nComparison:

FC-M

MG

Period:un

specified

;opportun

isticscreen

MSU,F

Cgroup

:clients

screen

ed;8,607,

1,312;

mea

nag

e(SD):51.2(10.4),

51.4

(10.4);first-screen

:48%,2

6%

Results

reported

forMSU,F

C:

Detectedcases:n¼37

,n¼9,oddsofb

reast

cancer

detectionissimilarbetwee

nMSUan

dFC:c

rudeOR:1.60(CI:0.77–3.32

);ad

justed

ORforsociodem

ographicfactors

(1.56,C

I:0.73–

3.31).

4.3

(MSU)

6.9

(FC)

Carkaci

etal.

(2013),

USA(17)

Qua


MMAT:75

%

Target:women

�35ye

arsin

Texas

Test:film

MMG(2009–10),digital

MMG

(2011–12);M

SUtype:

1van

Period:2009–2012

(4ye

ars);opportun

istic

screen

12,726

exam

s;33

%med

ically

underserved

population

Abno

rmal

callrate

¼16.2%

(film

)15.8%

(digital)

Detectedcases:no

treported

Operationa

lmea

sures:mea

nnu

mber

of

exam

sper

day

¼23

(film

),20

(digital);Mea

ndaily

kilometers¼

42km

Totalc

ost

per

MU¼

$427

,103(2013

USD)

2.3(film

,2009),

2.9(digital,

2011)

Fonten

oyet

al.

(2013),

Can

ada(14)

Retrospective

coho

rt

MMAT:100%

Objective:

toco

mparediagno

stic

perform

ance

ofMSUsto

FCs

Target:Women

ages

50–6

9in

Qu� eb

ecTest:MSU-M

MG(digital

andfilm

);MSU

type:

2vans,1

portab

leun

ittran

sportby

boat/plane

Comparison:

FC-M

MG

Period:20

02–

2010

(9ye

ars);results

reported

for20

02–

2006;organ

ized

program

MSU,F

Cgroup

:16,654

exam

s,1,0

00,706exam

s;mea

nag

e(SD)¼

57.9

(5.5),58

.0(5.5)

MSUsco

veragerate:4

4.3%

(2002–

05),

63.4%

(2006–10);first-screen

(MSU):11%

Results

ofMSU,F

C:

abno

rmal

callrate:8

.1%(n

¼1,3

54),9.5%

(n¼

95,440)

Detectedcases:n¼

72,n

¼5,166

Testsensitivity:

69.9%,7

0.3%;TestPPV:

5.3%

,5.4%

� Nodifferences

invalid

itymea

suresbetwee

nMSUan

dFC(compared

usingad

justed

risk

ratioswith95%

CI)

4.3

(MSU)

5.2(FC)

(Continue

donthefollowingpag

e)

Greenwald et al.




Table

3.Descriptive

summaryofqua

lity,

perform

ance

indicators,a

ndcase

detectionrates(Cont'd)

Autho

r,ye

ar,

coun

try,

Stud

ydesign

MMAT

qua

lityscore


tion

(studyobjective,

target

population,

screen

ingtest,MSU

type,

timeperiodof

stud

y)

Sample

(num

ber

ofclients

screen

edorex

ams,

dem

ographics)

Rep

orted

canc

erscreen

ingperform

ance

indicators

Can

cer

detec

tion

rate/1,000

exam

s

Brooks

etal.

(2013),

USA(42)

Qua


MMAT:75

%

Target:w

omen

ages

40–75inLo

uisville,KY

at"highrisk"(reg

ions

withhighcancer

mortalityan

dpove

rty)

Test:digitalMMGan

dCBE;M

SUtype:1v

anPeriod:2008–2

010

(3ye

ars);opportun

istic

screen

3,923

clientsscreen

ed(4,542MMG,4

,516

CBE);

mea

nag

e¼

54.6;29

%�

5ye

arssincelast

exam

Abno

rmal

callrate:9.3%

(n¼

424

)a

Detectedcases:n¼

31;T

estPPV:7

.3%

(31/424

)a

Factors

associated

withab

norm

alexam

:ag

e(<50

),no

insurance,

Hispan

icethn

icity,

smoking

,and

family

history

7.9

Haikele

tal.

(2012),

Brazil(30)

Qua


MMAT:75

%

Target:women

ages

40–6

9in

S~ ao

Pau

lostate

Test:film

MMG;M

SUtype:multipha

sicvan

(alsooffered

Pap

test

forcervical

cancer)

Period:20

03–

2005(3

years);

opportun

isticscreen

10,521

clientsscreen

ed;

mea

nag

e(SD)¼

51(7.8);

First-scree

n:42%

Abno

rmal

callrate:9.4%;b

iopsy

rate:2.6%

Detectedcases:n¼

41;TestPPV:4.5%;

Biopsy

PPV:16%

Operationa

lmea

sures:mea

ndailynu

mber

of

exam

s¼

26.3

3.9

Rodrigue

z-Cue

vaset

al.

(2009),

Mexico(71)

Qua


MMAT:75

%

Target:Women

ages

�40residingin

MexicoCity'sFed

eral

District

Test:film

MMG;MSUtype:

7va

nsPeriod:20

05–

2006(2

years);

opportun

isticscreen

96,828

clientsscreen

ed;

Mea

nag

e(SD)¼

49.3

(8.5)

Abno

rmal

callrate:1%

(n¼

949)

Loss

tofollo

w-upam

ong

abno

rmal

exam

s:21%

Detectedcases:n¼

208;T

estPPV¼

27.7%

(208/949)a

Proportionofcasesdetectedin

situ

or

stag

eI¼

29.4%

2.1

Del

Turco

etal.

(2007),

Italy(18)

Retrospective

coho

rt

MMAT:75

%

Studyobjective:

compareperform

ance

mea

suresofdigital

andfilm

MMGs(both

offered

onMSU)

Target:Women

ages

50–6

9residingin

Florence

Testgroup

:digital

MMG;C

omparison

group

:film

MMG(m

atched

byag

ean

dradiologist)

MSUtype:

2vans

Period:20

04–2005(2

years);o

rgan

ized

program

Digital,fi

lmgroup

:Clients

screen

ed:n¼

14,385,

n¼

1438

5First-scree

n:12.2%,11.8

%

Results

ofdigital,fi

lmgroup

:Abno

rmal

callrate:4.3%

(n¼

618),3.5%

(n¼

498)

Recallrate

(poorqua

lity):0

.3%

(n¼

39),

0.5%

(n¼

72)

Detectedcases:n¼

104,n

¼84

TestPPV:15.9%,14.7%

ProportionDCIS:2

7.8%

(n¼

29),17.8%

(n¼

15)

c2testsshowed

differencebetwee

ngroup

s�

Digital,fi

lm:7

.4,

8.2

(firstroun

d)

7.2,

5.5(rep

eat

roun

ds)

Zap

paet

al.

(2002),

Italy(76)

Qua


MMAT:75

%

Studyobjective:Tomonitorthe

occurrence

ofinterval

breastcancers

Target:Women

ages

40–70(1970

–1990);

ages

50–70(post

1990)in

thedistrictof

Florence

Test:film

MMG;MSUtype:

1van

Period:1985–

1993(9

years);o

rgan

ized

program

80,13

4exam

s:(13,153first

roun

d,6

6,981repea

troun

ds)

Detectedcases:n¼

277

Proportionofscreen

-detectedin-situ:

6.5%

(18/277

)90inciden

cecasesdetected�3

yearsafter

negativeexam

Breastd

ensity

was

associated

withincrea

sed

risk

ofdev

elopinginterval

case

4.9

(firstroun

d)

3.17

(rep

eat

roun

ds)

Gorden

neet

al.

(2000),

Belgium

(78)

Qua


MMAT:50

%

Target:99,699women

ages

40–6

9residingin

theprovinceofLi� eg

eTest:film

MMG;MSUtype:

3va

nsPeriod:1992–

1998(8

years);o

rgan

ized

program

52,475

exam

s(29,918

clientsscreen

ed)

Mea

nattend

ance

rate

¼25

%;a

bno

rmal

call

rate:3.3%

(n¼

1,012);recallrate

(poor

qua

lity):0.7%

(n¼

343)

Detectedcases:n¼

207;

TestPPV:2

0.5%a

ProportionDCIS:16%

(n¼

30);tumors

<10mm:3

6%

(n¼

70)

3.9a

(Continue

donthefollowingpag

e)





Table

3.Descriptive

summaryofqua

lity,

perform

ance

indicators,a

ndcase


Autho

r,ye

ar,

coun

try,

Stud

ydesign

MMAT

qua

lityscore


tion

(studyobjective,

target

population,

screen

ingtest,MSU

type,

timeperiodof

stud

y)

Sample

(num

ber

ofclients

screen

edorex

ams,

dem

ographics)

Rep

orted

canc

erscreen

ingperform

ance

indicators

Can

cer

detec

tion

rate/1,000

exam

s

Frelix

etal.

(1999),

USA(35)

Qua


MMAT:75

%

Target:w

omen

�40inThe

Bronx

boroug

hofN

ewYork

city

(und

erserved

population)

Test:film

MMGþ

CBE;M

SUtype:

2va

nsPeriod:1994–9

5(16mos.);opportun

istic

screen

1,944clientsscreen

ed;

45.6%

uninsured

Abno

rmal

callrate:18.5%

(n¼

360);biopsy

rate:2

.5%

(n¼

49)

Compliancerate

among

biopsy

reco

mmen

dations:100%

Detectedcases:n¼

26;testPPV:6.9%a;

biopsy

PPV:5

1%ProportionDCIS:16%

(n¼

4);stag

eI:36

%(n

¼9)

13.3a

Kan

net

al.

(1998),

USA(82)

Qua


MMAT:75

%

Target:W

omen

�40in

Long

Island

,New

York

Test:film

MMGan

dCBE;M

SUtype:

1va

nPeriod:1990–1994(5

years);o

rgan

ized

program

19,280exam

sBiopsy

reco

mmen

dationrate:1.5%(n

¼29

5);

biopsies

perform

ed:0

.8%

(n¼

157);L

oss

tofollo

w-up:46.8%

(n¼

138)

Detectedcases:n¼64;PPVreco

mmen

ded

&perform

edbiopsies:21.6%

&40.8%a

Operationa

lmea

sures:30

testsoffered

per

day

3.3a

Hortonet

al.

(1996),

UK(66)

Prospective

coho

rt

MMAT:50

%

Target:w

omen

ages

65–

74in

Ham

stea

d,

UK,n

otroutinelyinvitedto

breastcancer

screen

ingthroug

htheNationa

lHea

lth

Service

(NHS)

Test:film

MMG;M

SUtype:

1va

nComparison:

women

ages

50–6

4invited

forscreen

ingbytheNHS

Period:1992–

1993(0.5

year);organ

ized

program

4,576

clientsscreen

edResultsforag

egroup

s:50

–64,65–

69,70–7

4respective

lyAbno

rmal

callrate:3

.2%

(n¼

92),4

.1%(n

¼32

),4.8%

(n¼

44)

Biopsy

rate:0

.5%(n

¼14),1.6

%(n

¼12),1.5

%(n

¼14)

Detectedcases:n¼

13,n

¼11,n

¼12

TestPPV:14.1%

,34.4%,2

7.3%

a

Biopsy

PPV:92.9%,9

1.7%,8

5.7%

a

4.5

(50–6

4ye

ars;

14.2

(65–

69

years);

13.2

(70–74

years)

S� eg

uret

etal.

(1995),

France(72)

Qua


MMAT:100%

Target:5

2,617

women

ages

40–70in

Herau

ltregion,

France

Test:film

MMG;M

SUtype:

1va

nPeriod:1990–1992(2.5

years);organ

ized

program

26,026

clientsscreen

edScree

ning

cove

ragerate

¼48%

Abno

rmal

callrate:7

%(n

¼1,8

26);loss

tofollo

wup

among

recalls

¼10.6%;B

iopsy

rate:

1.5%

(n¼

393)

Detectedcases:n¼137;reported

PPV(8.4%)

based

onclientswho

returned

forfollo

w-up;

TestP

PV:7.5%a;Biopsy

PPV:35%

;Proportion

casesinsitu:18%(n

¼27

);tumors<1

cm:42%

;Detectedintervalcancerswithin30

mos.:n

¼13

5.3

Van

Oye

net

al.

(1994),

Belgium

(74)

Qua


MMAT:75

%

Target:5

7,33

9women

ages

50–6

4in

Antwerpan

dLimburgprovinces

Test:MMGno

totherwisespecified

MSUtype:

1semi-mobile

unit

(mam

mography

machine

,transported

inan

adap

tedtraileran

dsetup

inacentral

clinicin

each

visitedtown)

Period:1989–1992(4

years);o

rgan

ized

program

16,017

clientsscreen

edScree

ning

cove

ragerate

¼28

%;A

bno

rmal

callrate:4.1%

(n¼

652

);Lo

ssto

follo

wup

among

abno

rmal

calls:15%

Biopsy

rate:0

.6%

(n¼

89)

Detectedcases:n¼

46;T

estPPV:8.3%

(rep

orted

);TestPPV:0.071

a;Biopsy

PPV:

51.7%

ProportionDCIS:30%;stage1(<2

cm):59

.5%

Med

iantimefrom

screen

ingto

diagno

sis:

4wee

ksOperationa

lmea

sures:45exam

soffered

daily

2.9

(Continue

donthefollowingpag

e)

Greenwald et al.




Table

3.Descriptive

summaryofqua

lity,

perform

ance

indicators,a

ndcase


Autho

r,ye

ar,

coun

try,

Stud

ydesign

MMAT

qua

lityscore


tion

(studyobjective,

target

population,

screen

ingtest,MSU

type,

timeperiodof

stud

y)

Sample

(num

ber

ofclients

screen

edorex

ams,

dem

ographics)

Rep

orted

canc

erscreen

ingperform

ance

indicators

Can

cer

detec

tion

rate/1,000

exam

s

Garas

etal.

(1994),

Greece(73)

Qua


MMAT:100%

Target:4

2,411women

ages

40–6

4in

the

Iliaan

dMessiniaco

unties,southe

rnGreece

Test:film

MMG;M

SUtype:

1va

n(m

ultimodal,a

lsoprovided

Pap

tests,

resultsun

reported

)Period:4

years;organ

ized

program

22,258

clientsscreen

edScree

ning

cove

ragerate

¼52

.5%;A

bno

rmal

callrate:5.3%

(n¼

1169);biopsy

rate:0.8%

(n¼

176)(recommen

ded

),0.7%

(n¼

158)

perform

ed,loss

tofollo

w-up:11%

Detectedcases:n¼

69;testPPV:7.4%;

biopsy

PPV:4

7.1%

ProportionDCIS:4.3%;stage1(<2cm):51.5%

3.1

Dershaw

etal.

(1992),

USA(55)

Qua


MMAT:75

%

Target:w

omen

age�3

5inNew

York

state

Test:film

MMG(Pap

testsalso

offered

,resultsno

treported

bystud

y)MSUtype:

1va

n,2semi-mobile

MMGun

its

Period:1988–1991(3

years);o

pportun

istic

screen

22,540exam

sAbno

rmal

callrate:11.2

%(n

¼25

15);biopsy

reco

mmen

ded

rate:0

.6%

(n¼

288);biopsy

perform

edrate

Detectedcases:n¼

50;testPPV:2.0%;

biopsy

PPV(recommen

ded

):17.3%;b

iopsy

PPV(perform

ed):21%

Operationa

lmea

sures:25

exam

soffered

daily.C

osts(U

SD1992):a

verageco

stper

test

¼$65;

startupco

sts$36

0,000;

2.2

McC

oyet

al.

(1992),

USA(36)

Qua


MMAT:50

%

Target:w

omen

age�4

0in

Florida

(socioecono

mically

disad

vantag

ed)

Test:film

MMG(Pap

testsalso

offered

,resultsno

treported

bystud

y);M

SUtype:1

van

Period:1987–

1991(4

years);o

pportun

istic

screen

12,456

clientsscreen

ed;

First-scree

n:72

%Abno

rmal

callrate:2

1.3%

(n¼

2,660)

Detectedcases:n¼

90,testPPV:4

.0%a

ProportionofcasesDCIS:10%

(yea

rs1987–

89),24

%(yea

rs1990–9

1)

6.6

(preva

lent

rate)

5.5(ove

rall

rate)a

Tab

aran

dGad

(1981),

Swed

en(22)

RCT

MMAT:100%

Target:4

7,000women

age�4

0Ostergotlan

dco

unty,Swed

en;M

SUtype:1

van

Test:film

MMG;c

ontrol:no

screen

ing

(22,000women

inKopparbergco

unty)

Period:1977

–1980(3

years);o

rgan

ized

program

34,18

7clientsscreen

edScree

ning

cove

ragerate

among

interven

tion

group

:84.3%

Abno

rmal

callrate:4

.8%

(n¼

1655

);biopsy

rate:0

.1%(n

¼36

2)Detectedcases:n¼

235;

TestPPV:14.2%a;

biopsy

PPV:6

4.9%a

6.9

a

Strax

(1973

),USA(23)

RCT

MMAT:50

%Target:3

1,000women

age40–6

4participatingin

theHea

lthInsurancePlan

(HIP)in

New

York

City

Test:film

MMGan

dCBE;M

SUtype:

1va

nco

ntrolg

roup

:noscreen

ing(31,0

00

women

rand

omly

matched

onag

e,throug

hHIP

program)

Period:1963–

1969(7

years);o

rgan

ized

program

20,211clientsscreen

edInterven

tiongroup

:scree

ning

cove

ragerate:

66%

Detectedcases:n¼

296;d

etectionrate

per

1,000PYs:2.72

70%

ofcaseswerewitho

utaxillaryno

dal

invo

lvem

ent

Comparisongroup

:Detectedcases:n¼28

4;

detectionrate

per

1,000PYs:1.8

645%

ofcaseswerewitho

utaxillaryno

dal

invo

lvem

ent

2.3

(Continue

donthefollowingpag

e)





Table

3.Descriptive

summaryofqua

lity,

perform

ance

indicators,a

ndcase


Autho

r,ye

ar,

coun

try,

Stud

ydesign

MMAT

qua

lityscore


tion

(studyobjective,

target

population,

screen

ingtest,MSU

type,

timeperiodof

stud

y)

Sample

(num

ber

ofclients

screen

edorex

ams,

dem

ographics)

Rep

orted

canc

erscreen

ingperform

ance

indicators

Can

cer

detec

tion

rate/1,000

exam

s

Cervical

Can

cer

Lorenzie

tal.

(2016),

Brazil(21)

Qua


MMAT:75

%

Objective:Toev

alua

tetheefficien

cyofthe

careHPVtest

indetecting

high-risk

HPVin

women

withno

precursorlesions

and

evalua

teperform

ance

asaprimary

screen

ingmetho

dTarget:w

omen

ages

18–8

5residingin

4states

ofSouth-Eastan

dCen

tral-W

est

Brazil

Cotesting:CareH

PVþ

Pap

-liquidbased

cytology(Pap

-LBC)

MSUtype:

1va

nPeriod:0

3–12/2012

(8mos.);opportun

istic

screen

3,068clientsscreen

ed;

Med

ianag

e(ran

ge)

¼47(18–8

5)

Testpositive

forHR-H

PV:10.0%

(n¼

307)

Abno

rmal

cytology:

total4

.3%

(n¼

132):

[ASC/A

GC-U

S:n

¼66,A

SC/A

GC-H

:n¼

13,

LSIL:n

¼38

,HSIL:n

¼15];

HR-H

PVpositivity

among

cytologysamples:

8.2%

ofno

rmal

samples,39

.4%

ofASC/

AGC-U

S,38.5%ofA

SC/A

GC-H

,55.3%

ofLSIL,

100%

ofHSIL

Colposcopyrate:10.8%

referred

(n¼

332);

3.6%

perform

ed(n

¼111);6

6%

loss

tofollo

w-up

Biopsy

rate:2

.1%(n

¼66),CIN1:40.9%

(n¼

27);CIN2:

7.6%

(n¼

5);C

IN3:

6.1%

(n¼

4);inva

sive

carcinoma:

4.5%

(n¼

3)HPVtest:S

ensitivity:100%

(CI:75

.3–100%),

specificity:10.8%

(CI:5.1–19.6%)

1inva

sive

cancer/1,000

women

cotested

Pae

ngchitet

al.

(2014),

Tha

iland

(25)

Qua


stud

y

MMAT:100%

Objective:

describeprevalencean

dgen

otypedistributionofHPVin

Lampan

g,

Tha

iland

Target:w

omen

ages

30–7

0Test:Pap

-LBC,H

R-H

PVtesting;M

SUtype:1

van

Period:0

1–03/20

13(3

mos.);opportun

istic

screen

2,000clientsscreen

ed;

Mea

nag

e(ran

ge)

¼47.8(30–70)

Testpositive

forHR-H

PV:5.4%

(CI:4.5–6

.5;

n¼

108)

Rateofab

norm

alcytology:

1.95%

(1.4–2

.7)

Num

ber

withHSIL

orhighe

r:n¼

19HR-H

PVpositivity

among

cytologysamples:

4.0%,6

0.0%,8

9.5%

among

norm

al,

ASC-U

S/LSIL,H

SIL

respective

ly

9.5

HSIL/1,000

smea

rsa

Fregna

niet

al.

(2013),

Brazil(27)

Cross-sectiona

lan

alytic

MMAT:100%

Test:Pap

,comparison:

Pap

LBC

MSUtype:

1va

nPeriod:0

5–12/2010

(8mos.);opportun

istic

screen

Pap

,Pap

-LBC

Clientsscreen

ed:6,047,

6,001

Mea

nag

e(SD):46.1(13.1),

46.5

(12.5)

ResultsforPap

,Pap

-LBC:A

bno

rmalcallrate:

0.021,0

.01;

Specim

enad

equa

cyrate:9

9.92%

,99.97%

ASCUS-U

S:0.1%

(n¼

6),0.7%

(n¼

39);

ASC-H

:0.3%

(n¼

21),0.4%

(n¼

24);LS

IL:

0.3%

(n¼

19)vs

0.7%

(n¼

41);

HSIL:0

.2%

(n¼

14)vs

0.4%

(n¼

22)

RateofH

SILper

1,000sm

ears:

2vs.4

Swad

diwud

-hipong

etal

(1999),

Tha

iland

(20)

Mixed

:qua

litativecase-

stud

yþ

qua

ntitative

descriptive

MMAT:100%

Objective:mea

sure

effect

ofM

SUprogram

onkn

owledgean

dattitudes

toward

screen

ing

Target:low-incomewomen

residingin

ruralreg

ions

ofTha

iland

,ages

18–6

5Test:Pap

;MSUtype:

1va

n;Period:1992–

1996(5

years);O

pportun

isticscreen

13,081clientsscreen

ed;

Women

survey

edin

1991,

1994,1997:

n¼

1,603,

n¼

1,369,n

¼1,5

76

LSIL:n

¼46(0.4%);HSIL(%

):n¼46(0.4%);

detectedcases:n¼

7Surve

yresultsfrom

1991,1994,1997

Self-reported

knowledgeofPap

test:2

1%,

57%,7

6%

Self-reported

useofP

aptest:20%,58%,70%

0.5

cases/1,0

00

smea

rs3.5HSIL/1,000

smea

rs

Meg

evan

det

al.

(1996),

SouthAfrica

(15)

Prospective

coho

rt

MMAT:100%

Objective:

toiden

tify

operationa

lstrategiesto

minim

izeloss

tofollo

w-up

Target:low-incomewomen

inCap

etown

Test:(pha

seI)Pap

þColposcopyreferral

toFC;(pha

seII"See

,scree

n,trea

t"):Pap

þColposcopyin

MSU;M

SUtype:

1va

n;Period:1993(8

mos.);opportun

isticscreen

Pha

seI,II:

clients

screen

ed;2,619,2

,426

Mea

nag

e(ran

ge):3

4(19–8

3),3

1(17–

78);Total

First-scree

n:75

.2%

ResultsforP

hase

1,2:Abno

rmalPap

smea

rs-

LSIL:3

.3%

(n¼

87),3

.5%

(n¼

87);

HSIL:3

.2%

(n¼

86),1.3

%(n

¼33

)Effective

completionofco

lposcopyam

ong

HSIL:3

3%(29/86),97%

(32/33

)Operationa

lmea

sures:50

testsoffered

per

day

0.92/1,0

00

smea

rsa

(Continue

donthefollowingpag

e)

Greenwald et al.




Table

3.Descriptive

summaryofqua

lity,

perform

ance

indicators,a

ndcase


Autho

r,ye

ar,

coun

try,

Stud

ydesign

MMAT

qua

lityscore


tion

(studyobjective,

target

population,

screen

ingtest,MSU

type,

timeperiodof

stud

y)

Sample

(num

ber

ofclients

screen

edorex

ams,

dem

ographics)

Rep

orted

canc

erscreen

ingperform

ance

indicators

Can

cer

detec

tion

rate/1,000

exam

s

Tho

rntonet

al.

(1989),

UK(54)

Qua


MMAT:100%

Target:W

omen

>40em

ploye

dby

worksitesin

WestSurrey/North-East

Ham

pshireregion(U

K)

Test:Pap

,CBE(unrep

orted

);MSUtype:

1van

Period:1985–

1986(9

mos.);opportun

istic

screen

568clientsscreen

edCove

ragerate

among

women

intargeted

workplaces:91%

Abno

rmal

callrate:n

¼64(0.11);

Detectedcases:1;TestPPV:1.5

%a

1.76cases/

1,000sm

ears

Brind

leet

al.

(1976

),UK(49)

Qua


MMAT:100%

Target:w

omen

(ageun

specified

)residing

intheUK;Test:Pap

;MSUtype:

1van

Period:1973

(3mos.);opportun

isticscreen

1,526

clientsscreen

ed;

First-scree

n:70

%Abno

rmal

callrate:n

¼10

(0.66%)

6.6

abno

rmal/

1,000sm

ears

Whitfieldet

al(1972

),UK(50)

Qua


MMAT:N/A

Target:w

omen

(16–6

0)residingin

theUK

Test:Pap

(CBEalso

offered

,results

unreported

);MSUtype:

1va

nPeriod:1969–71(3

years);o

pportun

istic

screen

1,952

clientsscreen

ed;

first-screen

:70

%Num

ber

ofcasescarcinomain

situ:n

¼4

Cost

mea

suremen

ts(rep

orted

in1972

poun

ds(£)):

Costper

test¼£2,averag

eco

stper

detected

CIN3¼

£20

0

2.04casesof

carcinoma

insitu/1,000

smea

rs

Breast,

cervical

Mau

adet

al.

(2009),

Brazil(70)

Qua


MMAT:100%

Target:5

4,238

women

ages

40–6

9for

breastscreen

ing,117,239

women

ages

20–6

9forcervical

screen

ing

Test:Film

MMGan

dPap

MSUtype:

1van

Period:2

003–

2004(2

years);

opportun

isticscreen

MMG,P

ap:clients

screen

ed:7,192,

2,964;

First-scree

n:44%,7

%

Breast:screen

ingco

veragerate:13%

;Abno

rmal

callrate:7

.6%

(n¼

549);biopsy

rate:1.4%

(n¼

105);

Detectedcases:n¼22

;testP

PV:4%a;biopsy

PPV:2

0.9%a

Cervical:screen

ingco

veragerate:2.5%

Abno

rmalcallrate:1.9%(n

¼59

)a;cytologic

abno

rmalities:0.5%

(n¼

15):ASCUS0.1%

(n¼3);C

IN10

.13%(n

¼4);CIN20.1%

(n¼3);

CIN30.1%

(n¼

3);inv

asivesqua

mous

cell

carcinoma0.07%

(n¼

2);

operationa

lmea

sures:40exam

soffered

daily

Breast:

3.1cases/1,0

00

exam

sCervical:

0.7

cases/1,0

00

exam

s

Breast,

cervical,

prostate,

gastric,

oral,

colonan

dlung

Lynch(1976

),USA(94)

Qua


MMAT:50

%

Objective:

Mea

sure

effectiven

essofMSU

byco

mparingsurvival

withgen

eral

U.S.

population

Target:A

dults

residingin

ruralN

ebraska;

Test:un

specified

;MSUtype:

custom-built

house,

6m

�18

min

dim

ension

(transported

usingtractor)

Period:1971–1975

(5ye

ars);o

pportun

istic

screen

5,23

2clientsscreen

ed(1,984men

and3,24

8women

);Mea

nag

e(ran

ge)

¼55

(18–9

0)

Detectedcases:N¼

22(8

breast,7co

lon,

2en

dometrium

,1lung

,1prostate,

1pen

is,

1lip

,1stomach)

1cancer

diagno

sisper

238clientsscreen

edSurvival:observed

vs.exp

ecteddea

ths:3vs.

7.5(estim

ated

usingU.S.can

cermortality

rates)

4.2

cases/1,0

00

peo

ple

screen

ed

Breast,

cervical,

prostate,

gastric,

oral,

colon

skin,

pen

ile

Lynch,

(1973

),USA(67)

Qua


MMAT:25

%Target:ind

ividua

lsresidingin

eight

commun

itiesin

Neb

raska;

Test:MMG

(NOS),CBE,P

ap,D

VI,

proctosigmoidoscopy,

OVE,laryn

goscopy

MSUtype:

custom-builtho

use

(transported

bytractor)

Period:1971–1972

(2ye

ars);o

pportun

istic

screen

3,040screen

ingexam

s;Mea

nag

e¼60(m

ales),56

(fem

ales)

Totalnum

ber

ofm

aligna

ncies:n¼13

(n¼64

includ

ingskin)

Operationa

lmea

sures:16

patientssche

duled

per

hour

4.3

cases/1,0

00

peo

ple

screen

ed

Abbreviations:C

BE,clinicalbreastexam

;CI,95%

confiden

ceinterval;D

RE,d

igitalrectalexam

;DVI,directvisualinspection;

FC,fi

xed-cen

tre;Pap

,Pap

anicolausm

earwithco

nven

tiona

lcytology;Pap

-LBC,P

apan

icolau

smea

rwithliq

uid-based

cytology;

NOS,n

ototherwisespecified

;OVE,o

ralv

isua

lexamination;

VILI,visual

inspectionwithLu

goliodine.

aDen

otesha

ndcalculations.T

heobjectiveisleftun

specified

forstud

ieswhich

arepurelydescriptive

.Ifadistinctobjectiveoutsideofprogram

descriptionwas

men

tione

d,thisobjectivewas

stated

.See

Sup

plemen

tary

Tab

leS3forreferenceto

theMMATscale.





contexts. As displayed in Fig. 3, among 22 breast cancer screeningstudies reporting performance measures, case detection ratesranged from 2.15 to 14.65 per 1,000 mammography exams. Inthese studies, patients with abnormal screening results wererecalled to fixed clinics for further clinical work-up and diagnosticexams. The broad range in detection rates may be due to differ-ences in contextual factors between programs such as the ages ofscreened women, proportion of never-screened women, or differ-ences in incidence rates of breast cancer in various settings.

Twelve studies described cervical cancer MSU programs involv-ing screening exams performed by nurse technicians including:conventional or liquid-based Pap cytology, HPV testing, andvisual inspection with acetic acid (VIA); one MSU also offereddiagnostic colposcopy exam performed by a clinician (15). All 10multiphasic programs reported screening for cervical cancer.Notably, many of the cervical cancer screening studies were inlow-resource settings inBrazil, Peru, SouthAfrica, India, Thailand,and Taiwan (15, 20, 21, 24–27). The studies report diverse out-comes of detection of precancerous cervical lesions and invasivecancer, as described in Table 3. Because of the inconsistency ofreporting measures used, no summary figure of case detection ispresented for the cervical cancer screening studies.

Mechanisms for increasing delivery, access, and demand forscreening

Examples of operations of MSUs in regions distant fromcentralized services include cervical cancer screening in tents inthe Andes Mountains of Peru (26); a mammography unit trans-ported by boat and plane to reach Arctic regions in Canada (14);an MSU mammography program serving residents of 26 inhab-ited islands in Scotland (28); a semi-mobile colonoscopy pro-gram for high-risk individuals in South Africa residing over500 km away from the nearest hospital (29); and MSU interven-tions for breast and cervical cancer in the rural interior andAmazonian states of Brazil (21, 30). In addition, MSUs fill aunique niche in urban areas by targeting underscreened groupswho may be within a reasonable physical proximity to a fixedclinic, but less likely to access services due costs, awareness, andperceived barriers (26, 31–37).

Key factors to the accessibility of services are the time anddistance traveled to a screening center. Some studies reportedpatients' travel to the MSU location to be fairly minimal, withaverage distances traveled by clients to reach MSU sites of 4.5–34 km (38–40). One study from the United Kingdom foundMSUs were located substantially closer to patients than

Figure 2.

Assessment of risk of bias by study design. Review authors' judgments about each methodologic criterion are presented as percentages across the 22 studiesof quantitative descriptive design (A) and 7 studies of nonrandomized observational design (B). Judgments were based on criteria outlined in the MMAT(Supplementary Table S3).

Greenwald et al.




fixed clinics; themean distance per client to anMSUwas 6.4 kmascompared with fixed clinics that were on average 18.2 kmaway (41).

Community access to screeningSeveral MSU programs aimed to increase community access to

screening (24, 34, 42–48). An increased screening rate from44.3% to 63.4% was reported in regions served exclusively byMSUs in Quebec, Canada over a course of eight years (14). A Thaistudy found an increase in the proportion of women reportingever receiving a Pap smear from 20% in 1991, to 70% in 1999 dueto MSU operations (20).

In cases where before and after measures of screening uptakewere unavailable, using the proportion of never-screened indivi-dualswho received theirfirst screening exam through the programcan serve as a surrogate measure for increased access. Amongbreast screening programs, studies reported the proportion offirst-screen clients to range from11%to72%(18, 30, 36).Cervicalcancer screening programs targeting low-income groups reachedparticularly underserved populations composed of 75% never-screened clients in South Africa (15), and 70% never-screenedclients in the United Kingdom (49, 50).

MSU programs have addressed economic barriers to screeningby reaching underserved populations. Notably, 31% (n ¼ 24) ofstudies offered screening services free of charge. The majority ofstudies that discussed fee-for-service economic barriers to screen-ing were based in the United States where no organized breastcancer screening program existed and attending screening waslikely to be affected by insurance status (17, 34, 35, 42–44, 47,48, 51–53). Furthermore, a number of MSU programs have de-creased structural barriers by offering screening at the workplace(49, 54–58), shopping centers (50), and retirement homes (59).

Client demandClient demand for screening is an essential part of attaining

population-level screening coverage. MSU qualitative studiesused focus groups and surveys to identify women's attitudestowards screening, their perception of the utility of screening andintent to screen (28, 38, 39, 46, 60–64). Among women surveyedfollowing MSU screening, nonadherence to screening guidelineswas reported as related to a lack of awareness of early detection,lack of accessible information, negative beliefs or attitudes toward

screening, as well as fear of discomfort/embarrassment, cost, andbad news (34, 61, 63).

Studies reported high levels of overall client satisfaction withthe quality of service (24, 62, 64) and adequate levels of comfortand privacy with screening (24, 62, 65). Two studies measuredpatient preferences and documented preference for MSU relativeto fixed-site clinic (24, 62). In contrast, one study reported a lowerclient satisfaction for MSUs relative to hospital screening in termsof receipt of test results, staff interpersonal skills, privacy, physicalsurroundings, and general satisfaction (64).

Studies described various methods to promote screeningattendance, including direct invitation by mail or telephone,publicity (flyers, radio, car loudspeaker, newspaper), word ofmouth, or physician referral (32, 38, 49, 62, 66–69). A studyconducted during the initial implementation of a breast andcervical cancer screening program in Brazil found that amongvarious promotion strategies, community health care agentsmaking home visits was the most effective means of recruitingwomen to begin screening (70).

Determinants of successful follow-upCompliance to the recommended follow-up of an abnormal

screening exam serves as an indicator of the quality of a screeningprogram. Rates of loss to follow-up generally tended to be higherin low andmiddle-income countries. A 21% loss to follow-up rateof the MSU mammography screening program in Mexico City(71) and a 66% loss to follow-up for colposcopy referrals in theMSU cervical cancer screening program in Brazil (21) were foundcompared with a 10%–15% loss to follow-up in the MSU breastscreening programs in France (72), Greece (73), and Belgium(74). MSU operations should strive to minimize potential delaysin the referral pathway and loss to follow-up thatmayoccur due toa delay between the screening test and dissemination of results/availability of treatment. A cervical cancer screening study inSouthAfrica assessed the effect of a "see, screen, treat" interventionto minimize loss to follow-up and found improved rates ofcompleted follow-up when clients with suspected lesions werereferred to theMSU for diagnostic colposcopy and lesion excision(15). Ninety-eight percent of patients with high-grade squamousintraepithelial lesions (HSIL) attended MSU colposcopy as com-paredwith33%complete follow-upwhen referred for colposcopyat the nearest hospital, which was 30 km away from theMSU site.

Strax (1973), USAFrelix et al. (1999), USA

Brooks et al. (2012), USAHorton et al. (1996), UK

McCoy et al. (1992), USATabar and Gad (1981), Sweden

Del Turco et. al. (2007), ItalyAl Mulhim et al. (2015), Saudi Arabia

Séguret et al. (1995), FranceRenck et al (2014), Brazil

Fontenoy et al. (2013), CanadaGordenne et al. (2000), Belgium

Haikel et al. (2012), BrazilApffelstaedt et al. (2014), South Africa

Zappa et al. (2002), ItalyKann et al. (1998), USA

Garas et al. (1994), GreeceHughes et al. (2014), Australia

Carkaci et al. (2013), USAVan Oyen et al. (1994), Belgium

Dershaw et al. (1992), USARodriguez-Cuevas et al. (2009), Mexico

0.00 2.00 4.00 6.00 8.00 10.00 12.00 14.00 16.00Number of cases detected per 1,000 screening mammograms

Figure 3.

Breast cancer case detection rates perstudy among the subset of breastcancer studies reporting performanceindicators (n ¼ 22). Crude casedetection rates corresponding to thenumber of detected cases of cancerper 1,000 mammography exams arepresented.





DiscussionThis review summarizes the evidence regarding the feasibility of

MSU interventions for the early detection of cancer. We describedexisting programs, their performance, and the mechanismsthrough which they can increase the delivery, access, and demandfor screening services. It was evidenced that MSUs can increaseaccess for underscreened groups. Offering early detection servicesthrough MSUs is a practical way for service providers to increasephysical and economic access to screening while reducing barriersfor clients (structural barriers and out-of-pocket costs).

However, there are several challenges and risks involved withoffering screening via MSUs as compared with fixed clinics.Referral systems and challenges with follow-up are a major issue.In an MSU setting, the exam is generally conducted by a nursetechnician on the MSU and any abnormalities that are foundupon interpreting the exam, will require the patient to travel to afixed clinic to visit a physician on a separate date, whereas a fixedclinicmay have the flexibility to conduct a diagnostic examon thesameday andminimize potential losses to follow-up. In addition,MSUs face unique risks when compared with fixed clinics—poorroads may necessitate the recalibration of sensitive diagnosticmachinery if transported by MSU. Finally, client perceptions ofMSUs may differ from fixed-clinics, as MSUs are generally per-ceived as less clinical than hospital-based clinics. This review didnot focus on the clinical considerations of screening tests withrespect to their effectiveness in reducingmorbidity ormortality forcancer sites. However this serves as an area for future study todetermine whether MSUs are as clinically effective as fixedfacilities.

The body of evidence summarized by these studies is modest.The study designs were largely descriptive single-group studies,with few high-quality observational studies and RCTs document-ing the performance of MSUs, the latter type representing thehighest level of evidence, followed by observational studies anddescriptive studies (75). Among studies that were appraised formethodologic quality, we found a low risk of bias for measuresincluding sampling, selection bias, and valid measurements.However, several studies weremethodologically weak and at highrisk of bias for the incomplete reporting of outcome measures.Therefore, although the overall methodologic quality of thestudies summarized by our review was at a moderately low riskof bias, the strength of evidence continues to be limited. Aweakness of this quality review is that some studies scoreddecently on the MMAT scale, despite shortcomings in design andreporting.We found theMMAT scalewas restrictivewith respect toscoring the methodologic quality of screening studies. The designand methods employed by future studies of MSUs should payparticular attention to reporting of complete outcomes.

There are potential risks associated with screening in general,particularly if the test and the medical procedures that arerequired in consequence are inefficiently administered. Thisincludes the potential for missing cancers (false negatives) andpatients undergoing unnecessary clinical follow-up if they testpositive but do not have the disease (false positives). Regret-tably, risks of screening may be worsened in settings wherefollow-up is limited, because individuals with abnormal testsmay not return and the period between screening rounds mayextend beyond the recommended intervals, thus permittingdevelopment of interval cancers. Few studies reported thepotential for false negative test results which can be measured

as the number of interval cancers occurring within 24 monthsof a negative test result or by reporting test specificity (13, 21,72, 76). Using a descriptive single-group study design measur-ing rates of cancer detection at baseline (cross-sectional), andwithout follow-up data, it is not possible to assess the rates offalse-negative results. With respect to prevalence of false posi-tives, due to the wide ranges of reported positive predictivevalues of tests and the lack of reporting on confoundingcharacteristics in the study population (most notably age) itwas not possible to summarize rates of false positives acrossstudies.

The findings of individual studies have limited generalizability.The quantitative findings in terms of test performance cannot bedirectly compared between studies or generalized to other settingsdue to differences in baseline risk of cancer and the non-reportingof age-standardized detection rates. The qualitative outcomessuch as the acceptability of a given cancer screening test and clientsatisfaction levels with MSU services are also highly contextual,and cannot be generalized across studies.

Insufficient evidence was available to describe the cost-effec-tiveness of MSU interventions but we hypothesize that MSUshave lower start-up costs compared with fixed sites but may facegreater maintenance costs for technology and equipment due tostress caused by road travel. Conducting studies to investigatethe cost-effectiveness of MSU programs relative to fixed clinicsshould be a priority.

The MSU studies included in this review were not restrictedby study design, types of screening tests used, or types ofoutcomes reported. This broad inclusion criterion is both astrength and a limitation of this review. Studying multiple MSUinterventions emphasized the versatility of MSU programs butlimits the depth of analysis for performance outcomes ofindividual programs. The literature search was limited to pro-grams that explicitly described the methods of screening asmobile or used a synonym listed within the search (Supple-mentary Table S1). The search was designed to be as robust anddetailed as possible. However, it is possible that some studieswere overlooked. Publication bias may have led to nonpubli-cation of MSU studies of high and poor quality that do notreport their findings in peer-reviewed journals. This review wasonly able to synthesize published results.

This review synthesizes the available knowledge regardingMSUinterventions for cancer screening. MSUs can be an importanthealth system component to expand screening coverage to ruralareas or to urban residents who fail to be reached by healthpromotion messages or lack medical insurance. Overall, ourfindings highlight the value of MSU interventions, specificallywith respect to increasing access to early detection services. Moreevidence is needed to provide comparative information on thecost-effectiveness and effectiveness of MSU interventions as com-pared with fixed-clinics to inform decisionmaking for health careproviders or policymakers.

Disclosure of Potential Conflicts of InterestNo potential conflicts of interest were disclosed.

The costs of publication of this articlewere defrayed inpart by the payment ofpage charges. This article must therefore be hereby marked advertisement inaccordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received June 18, 2017; revisedAugust 9, 2017; accepted September 27, 2017;published OnlineFirst October 4, 2017.

Greenwald et al.




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Cancer Mobile Screening Units for the Early Detection ... · Review Mobile Screening Units for the Early Detection of Cancer: A Systematic Review Zo€e R. Greenwald 1,2, Mariam El-Zein2,