Received 11/1/96; revised 3/18/97; accepted 3/19/97.

The costs of publication of this article were defrayed in part by the payment of

page charges. This article must therefore be hereby marked advertisement in

accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

I This work was supported by Grants CA55769 (to M. R. S) and CA68437 (to

W. K. H.).2 To whom requests for reprints should be addressed, at Department of Epide-

miology, Box 189, The University ofTexas M. D. Anderson Cancer Center, 1515Holcombe Boulevard, Houston, TX 77030.

Vol. 6, 565-571, Augur: 1997 Cancer Epidemiology, Biomarkers & Prevention 565

Identifying and Recruiting Healthy Control Subjects from a Managed

Care Organization: A Methodology for Molecular Epidemiological

Case-Control Studies of Cancer1

Karen Suchanek Hudmon, Susan E. Honn, Hong Jiang,

Robert M. Chamberlain, Wenguang Xlang, George Ferry,

Wayne Gosbee, Waun Ki Hong, and Margaret R. Spi&

Departments of Epidemiology [K. S. H., S. E. H., H. J., R. M. C., W. X.,

M. R. S.], Behavioral Science [K. S. H.], and Thoracic Head and Neck Medical

Oncology [W. K. H.], The University of Texas M. D. Anderson Cancer Center,

and Kelsey Seybold Foundation [G. F., W. G.], Houston, Texas 77030

Abstract

Case-control studies with stringent matching criteria

require large pools of healthy subjects from which toselect matched controls. This paper describes a successful

method of identifying a large pool of potential control

subjects to participate in two molecular epidemiological

case-control studies of lung cancer, each enrolling 400case subjects and 400 control subjects. These studies are

not population based, and the study base is not well-

defined. Therefore, potential control subjects are beingidentified and recruited through 20 area clinic sites of a

large multispecialty health maintenance organization.

Because the research focus is driven by genetic

hypotheses and we are controlling for multiple smoking-

related variables, representativeness is of lesser concern.

To identify potential control subjects, a one-page

questionnaire is distributed to patients in the waitingroom to assess contact information as well as data

relevant to the case-control matching process. An average

of 2,228 questionnaIres are returned monthly toward a

target pool of 40,000; of these, 59% of the respondents

fuffill eligibifity criteria as a control subject for one of the

studies and are not averse to being contacted in thefuture for the purpose of research. When compared to

former smokers and never smokers, current smokers in

the control population were least likely to refuse further

contact. A collaborative arrangement with a managed

care organization offers a feasible mechanism through

which researchers can access a large, ethnically diverse

population of potential control subjects.

Introduction

Although there is a growing body ofliterature describing meth-

ods of recruitment and factors associated with participation in

clinical trials, less is known about these issues as they pertain

to epidemiological case-control studies. Molecular epidemio-logical studies require active consent from participants because

biological samples, in addition to personal interview data, must

be collected. The identification of case and control subjectstypically requires separate recruitment methodologies, andwhen matching criteria are stringent, it is necessary to establish

a large population of eligible subjects from which to select

controls. Logistically, the conduct of large case-control studies

can be difficult, costly, and time consuming.

The number and type of molecular epidemiological case-

control studies being conducted is growing rapidly. Although

the literature is replete with discussions of the pitfalls in controlselection, little methodological guidance is available for epide-

miologists who must identify and recruit healthy persons to

serve as control subjects for large case-control studies, espe-

cially when the cases are hospital-based and the study base is

not well-defined. This paper describes a method for developinga large pool of approximately 40,000 control subjects from

which to select participants for two hospital-based molecularepidemiological case-control studies of lung cancer: Genetic

Markers of Cancer Susceptibility in Former Smokers (the “For-

mer Smoker Study”) and the Ecogenetics of Lung CancerStudy. Control subjects are being identified and recruitedthrough a large, multispecialty health maintenance organiza-

tion. Additionally, we describe our methods of identifying case

subjects, sociodemographic factors that affect potential control

subjects’ willingness to participate, and agreement betweenwritten questionnaire and personal interview data among the

currently enrolled control subjects.The Former Smoker Study examines interindividual dif-

ferences in genetically determined susceptibility to tobacco

carcinogenesis in former smokers (i.e., individuals who stopped

smoking at least 1 year before cancer diagnosis), a group thatstill exhibits substantially increased risks for cancer when com-

pared with never smokers. The Ecogenetics of Lung CancerStudy extends the aims ofthe Former Smoker Study to examinesimilar susceptibility markers among current and never smok-

ers. Both studies are designed to assess lung cancer suscepti-

bility at several stages in tobacco carcinogenesis, includinggenetic modulation of carcinogen activation and detoxification

(metabolic polymorphisms), in vitro chromosome sensitivity totobacco mutagens, DNA repair capacity, and levels of tobacco-

related DNA adducts in current smokers.

Each study will accrue 400 lung cancer case subjects;

control subjects will be matched to case subjects in a 1 : 1 ratiowith respect to sex, age (±5 years), ethnicity, smoking status

(ever, never, and former), duration of smoking cessation in

566 RecruitIng Healthy Control Subjects

3 The abbreviations used are: UTMDACC, University of Texas M. D. Anderson

Cancer Center; KS, Kelsey Seybold.

former smokers (±5 years), and pack-year smoking history informer smokers (± 10 pack-years). To be included as a casesubject, individuals must be a minimum of 18 years old with a

histologically confirmed lung cancer who have not had chem-otherapy or radiotherapy within the preceding year. Case sub-jects are enrolled without regard to sex, ethnicity, cancer stage,or cancer histology. Control subjects must have no previoushistory of cancer, with the exception of nonmelanoma skincancer. The study has been described in detail previously (1).

Materials and Methods

Mechanisms for Identifying Case Subjects. Because cytoge-netic studies are being performed, recent prior chemotherapy orradiotherapy are exclusion criteria. Therefore, the challenge incase enrollment is early ascertainment, before initiation of

therapy.Although the majority of cases are being identified

through UTMDACC3 in Houston, procedures are in place foradditional case ascertainment through the KS Foundation andseveral hospitals in San Antonio (to enhance the Mexican-American proportion of cases) as well as the Ben Taub County

Hospital and the Veterans Affairs Hospital in Houston. Here,we describe the methods of case ascertainment at UTMDACC.

Staff interviewers conduct a daily review of computerizedappointment schedules for the hospital outpatient clinics thatserve lung cancer patients (thoracic medical and surgery din-

ics). Each new patient is asked to complete a brief questionnairethat assesses smoking status and prior therapy as well as the

individual’s interest in participating in an epidemiologicalstudy. Interviewers match the questionnaires with their com-

puterized listings to identify potentially eligible subjects. After

obtaining permission from the patient’s physician, interestedpatients are given an informational brochure, and the inter-viewer explains the study to the potential participant. Afterinformed consent is obtained, an in-depth interview is con-

ducted, and a 30-mI blood sample is procured and hand-deiv-ered to the epidemiology research laboratories for processing

and storage. Each patient who provides a blood sample andcompletes the interview receives a $20 voucher for use at a

local supermarket.

Selection of a Comparison Population. The principles un-derlying appropriate control selection have been well de-scribed (2-4). However, in practice, adherence to theseprinciples is often problematic and constrained by resources,time, and feasibility. Furthermore, these difficulties are mag-nified when the cases derive from an urban cancer center thatserves as a tertiary referral center. Wacholder et a!. (3) have

outlined the benefits and drawbacks of choosing medicalpractice controls. Because population-based control selec-tion was not considered an option for our research, we

decided to use the diverse catchment area of the largesthealth maintenance organization in the Houston metropoli-

tan area. This comparison population is not necessarily arepresentative sample of the population base of the cases and

may differ by socioeconomic status and other unmeasureddeterminants. However, our study design mandated closematching on smoking status; therefore, we are indirectly

matching on correlates of smoking behavior (e.g., education,

health behaviors, and others). Moreover, because our re-search focus was entirely driven by genetic hypotheses (i.e.,

cancer risk is associated with a susceptible, exposed sub-

population), representativeness was less of a concern than if

we were considering only environmental determinants of

lung cancer.

Mechanisms for Identifying Control Subjects. Because weare matching a comparison group on restrictive smoking criteria

as well as by age, sex, and ethnicity, our study requires a large

pool from which to select control subjects. Thus, healthy sub-

jects to serve as controls are being recruited through the KS

organization, with the assistance of the KS Foundation research

staff. KS is a large, private, multispecialty health-maintenance

organization that services capitated, Medicare, Medicaid, and

fee-for-service patients. The organization has provided clinical

services for over 50 years and has developed a large and

heterogeneous client base. Approximately 800,000 patient con-

tacts are recorded annually from approximately 250,000 mdi-

viduals enrolled in its Houston area clinics. The KS Foundation

is a not-for-profit organization that is interested in outcomes

research, clinical trials, and cancer prevention. We have estab-

lished a collaborative agreement with the KS clinics and Foun-

dation to identify, enroll, and interview a healthy comparison

population for our studies. It is our goal to identify 40,000 KS

enrollees to comprise the healthy subject pool from which we

will select matched control subjects.

We developed and pilot tested a one-page questionnaire

that elicits all relevant criteria for control selection and evalu-

ates participant interest. This form is distributed by KS person-

nel during registration at a scheduled appointment. Because the

questionnaire is attached to KS forms routinely distributed

during registration, we designed our form to be distinctly dif-

ferent from other KS forms (such as paper color and format).Patients are instructed to complete the questionnaire and de-

posit it in a designated collection box that has been placed

conspicuously in the clinic waiting area. The collection boxesare designed to coordinate with the questionnaire color and

style. A Plexiglas holder is attached to the box to hold pencils

and additional questionnaires that may be completed by persons

accompanying patients. Leaflets summarizing the study and

listing the telephone number ofthe project director are provided

with the collection boxes. Both the questionnaires and the

leaflets are printed in English on one side and Spanish on the

reverse side.

Prior to full-scale implementation across the 20 clinic

sites, the distribution methods were pilot tested in the largest

KS clinic site. The pilot study, conducted over a period of 4

weeks, provided feedback to refine the questionnaire and

method of distribution. The final questionnaire assesses: (a)

variables pertinent to the matching criteria for the case-control

study, including sex, date of birth, ethnicity, smoking status,

age at smoking initiation, age at smoking cessation (former

smokers), number of years smoked, number of cigarettessmoked per day, and history of previous cancer; (b) contact

information, including address and telephone number; and (c)willingness to be contacted for further questioning, posed by

the question,”Would you be willing to answer more questions

if contacted?” Subjects who respond either “yes” or “maybe”

are classified as potential participants. For the purpose of this

paper, willingness to be contacted will be considered as will-ingness to participate in one of the case-control studies. An-

other item, added for the benefit of the KS organization, in-quires if respondents would like to receive smoking cessation

materials from the KS health promotion department. The over-

all study and the final questionnaire have been reviewed and

1995 1996

Fig. I. Monthly accrual of questionnaires from KS clinic sites. The pilot phase

was conducted at KS’s largest clinic site. Initiation of questionnaire administra-

lion at the remaining 19 clinic sites occurred over the span of months 1-4. No

questionnaires were distributed between the pilot phase and month 1.

Cancer Epidemiology, Biomarkers & Prevention 567

approved by the Institutional Review Boards for the Protection

of Human Subjects at UTMDACC and KS.

Over a period of 4 months, questionnaire distributionprocedures were phased in at the remaining 19 clinic sites.

Each Thursday, a designated person at each clinic site for-wards all completed questionnaires to the KS Foundation.

Questionnaires are tallied by the KS staff and retrieved by amember of our study personnel on the following Monday. At

this time, the questionnaire data are routed through data

cleaning and consistency checks, followed by coding and

data entry. Questionnaires are entered into the project data

base within 7 days of their receipt, and variables that are

imperative to the case-control matching process are double-

keyed to ensure accuracy.Questionnaire accrual rates are monitored through

weekly reports that enumerate the number of questionnaires

obtained at each clinic site. Each Monday, KS is provided

with a report describing the previous week’s questionnaire

accrual number; on the second Monday of each month, themedical director of the KS Foundation receives the same

report as well as an aggregate report characterizing the study

population. These reports are generated weekly so that prob-lems in accrual may be identified and addressed rapidly. The

majority of feedback provided to the clinic sites is admin-

istered by the KS Foundation; however, our project coordi-

nator and a KS representative visit each site approximately

every 3 months to re-establish contacts and provide incen-

tives, thereby enhancing the study’s visibility.

For each case subject accrued, there is a computer-

generated list of up to five potential matched control sub-

jects. The selected control subjects are contacted by tele-

phone to confirm willingness to participate, and an

appointment is scheduled at a KS clinic site convenient to

the participant. At the designated meeting time, the control

subject is greeted by a KS or UTMDACC interviewer and

escorted to a KS phlebotomist who draws the necessary

blood sample. The interviews, which take approximately 1 h,

are conducted by a trained interviewer from the UTMDACC

study staff. Each participating control subject is compen-

sated with a $20 voucher for use at a local grocery store and

parking validation. The blood samples are delivered to the

epidemiology laboratory by the staff interviewer.

Analytic Procedures. Characteristics of the respondents are

summarized using descriptive statistics. For the analysis of

factors associated with willingness to participate among

eligible control subjects, a dependent variable (“willingness

to participate”) was created by combining subjects who

responded “yes” with subjects who responded “maybe” to

the questionnaire item, “Would you be willing to answer

more questions if contacted?” This resulted in a dichotomous

yes/no variable. Because smoking status was associated with

willingness to participate as well as multiple predictor van-

ables, analyses were stratified by smoking status (never,former, and current). Relationships with the dependent van-

able were assessed using x2 tests of independence for cate-

gonical variables and t tests for continuous variables. Among

former and current smokers, multivariate tests of associa-

tions between smoking-related variables and willingness to

participate were conducted using logistic regression, con-

trolling for sex, race, and age. For the 121 control subjects

who had been enrolled into the study at the time of manu-

script submission, we assessed concordance between the KSwaiting room questionnaire data and personal interview data.

2,000�0a)

i� 1,500C,)

CC.2 1,000

a)a-

.� 500a)

.0

E

z

Pilot 01 02 03 04 05 06 07 08 09 10 11

Month

All statistical procedures were conducted using SPSS forWindows, version 6. 1 (5).

Results

Accrual Rates for Control Population Questionnaires. As

described above, accrual to the pool of control subjects is

monitored over time. The KS Foundation is unable to pro-vide denominator data by clinic; therefore, actual responserates cannot be computed. Questionnaire accrual rates fluc-

tuate with seasonal variation in acute illnesses and holidaysand will decrease over time as the proportion of KS patientswho have already completed a questionnaire increases (be-

cause of repeat visits during the accrual period). Fig. Idepicts accrual of questionnaires over time, including ac-

crual during the pilot phase. Since initiation of questionnairedistribution at the final KS site (as of month 5), we havereceived an average of 2228 questionnaires each month. Acomparison of the cumulative statistics on a weekly basis

now shows little change in the summary statistics data as

new respondents are added to the pool of controls.

Characteristics of Questionnaire Respondents and Willing-ness to Participate. After 12 months of accrual (including I

month of accrual during the pilot phase), questionnaires havebeen received from 14,624 KS patients. Of these, 11,763(80.4%) provided sufficient data for subject contact andmatching purposes. There were 454 persons deemed ineli-gible to serve as a control subject because they had a per-sonal history of cancer other than nonmelanoma skin cancer.

As shown in Table 1, of 14,624 questionnaires received,8,691 (59.4%) of respondents: (a) have provided sufficientquestionnaire data for contact and matching purposes; (b)have no personal history of cancer other than nonmelanoma

skin cancer; and (c) are not opposed to participation in thestudy. The majority of eligible respondents were female(66.2%) and white (59.0%), with a mean age (SD) of 42.1(14.0). Over one-half never smoked, and 22.7% designated

that they formerly smoked but had quit.Current smokers were least likely to refuse participation

when compared with former and never smokers (Table I;18.7% refusal for current smokers versus 25.5% and 20.8%for never and former smokers, respectively; x2’ 2 df = 53.0,P < 0.0001). Table 2 shows the relationships ofsex, age, andrace with willingness to participate, stratified by smoking

568 RecruIting Healthy Control Subjects

Table I Characteristic

Variable

s of study-eligible KS questionnaire respondents who provided adequate data for contact and matching purposes, b

Smoking status

y smoking status

n 11,309Category Never smoker Former smoker Current smoker

n 6,599 n 2,572 n 2,138

Sex Male 1,813 (27.5r 1,180 (45.9) 834 (39.0)

Female 4,786 (72.5) 1,392 (54.1) 1,304 (61.0)

3,827 (33.8)

7,482 (66.2)

Race White 3,433 (52.0) 1,860 (72.3) 1,379 (64.5)

African-American 1,824 (27.6) 416 (16.2) 474 (22.2)

Hispanic 1,018 (15.4) 248 (9.6) 228 (10.7)

Other 324 (4.9) 48 (1.9) 57 (2.7)

6,672 (59.0)

2,714(24.0)

1,494 (13.2)

429 (3.8)

Age in years 18-39 3,631 (55.0) 708 (27.5) 1,067 (49.9)

40-49 1,605 (24.3) 672 (26.1) 598 (28.0)

50-59 727 (1 1.0) 515 (20.0) 296 (13.8)

60+ 636(9.6) 677 (26.3) 177 (8.3)

5,406(47.8)

2,875 (25.4)

1,538 (13.6)

1,490 (13.2)

History of cancer Cancer free 6,510 (98.7) 2,495 (97.0) 2,122 (99.3)

Nonmelanoma skin cancer 89 (1.3) 77 (3.0) 16 (0.7)

1 1,127 (98.4)

182 (1.6)

Willingness to Yes 2,870 (43.5) 1,359 (52.8) 1,142 (53.4) 5,371 (47.5)

participate Maybe 2,045 (31.0) 679 (26.4) 596 (27.9)

No 1,684 (25.5) 534 (20.8) 400 (18.7)

3,320(29.4)

2,618 (23.1)

a Number (percentage).

Table 2 Factors associated with willingness to participate: age, sex, and race, by smoking status

Smoking status Variable Category Willing Not willing P”

Never smokers Sex Male 1,328 (73.2)” 485 (26.8)

Female 3,587 (74.9) 1,199 (25.1)

Age 18-39 2,615 (72.0) 1,016(28.0)

40-49 1,237 (77.1) 368 (22.9)

50-59 571 (78.5) 156 (21.5)

60+ 492 (77.4) 144(22.6)

Race White 2,537 (73.9) 896 (26.1)

African-American 1,372 (75.2) 452 (24.8)

Hispanic 765 (75.1) 253 (24.9)

Other 241 (74.4) 83 (25.6)

0.16

0.00

0.71

Former smokers Sex Male 965 (81.8) 215 (1 8.2)

Female 1,073 (77.1) 319(22.9)

Age 18-39 552 (78.0) 156(22.0)

40-49 521 (77.5) 151 (22.5)

50-59 416 (80.8) 99(19.2)

60+ 549(81.1) 128(18.9)

Race White 1,492 (80.2) 368 (19.8)

African-American 319 (76.7) 97 (23.3)

Hispanic 190 (76.6) 58 (23.4)

Other 37 (77.1) 1 1 (22.9)

0.00

0.26

0.27

Current smokers Sex Male 684 (82.0) 150 (18.0)

Female 1,054 (80.8) 250(19.2)

Age 18-39 873 (81.8) 194 (18.2)

40-49 473 (79.1) 125 (20.9)

50-59 260 (87.8) 36(12.2)

60+ 132 (74.6) 45 (25.4)

Race White 1,084 (78.6) 295 (21.4)

African-American 421 (88.8) 53 (11.2)

Hispanic 182 (79.8) 46(20.2)

Other 51(89.5) 6(10.5)

0.49

0.00

0.00

a p associated with g� tests of independence.

b Number (percentage).

status. Among never smokers and current smokers, the pro-portions of men and women interested in participation were

similar. For former smokers, however, men were signifi-cantly more willing to participate than women (81.8% versus77.1%). Age was a significant predictor of willingness toparticipate among never smokers and current smokers, with

willingness being highest in individuals between 50 and 59years old. Race predicted willingness to participate only in

current smokers. Whites and Hispanics had similar refusalrates, which were nearly double the refusal rates for mdi-viduals of African-American or “other” origin.

Table 3 shows relationships of smoking-related variableswith willingness to participate. Controlling for sex, age, and

race, former smokers who did not refuse participation were

heavier smokers who had smoked for a longer duration. Incurrent smokers, persons who were not opposed to participation

0

Age stopped smoking (Na68)

-13-8 .6 -5 -4 -3 -2 -1 0 1 2 3 4 8 10141523

Discrepancy in years for reported age at smoking cessation

Number of cigarettes smoked per day (N63)

IDiscrepancy in reported number of cigarettes smoked per day

Cancer Epidemiology, Bioinarkers & Prevention 569

Table 3 Factors associated with willingnes s to participate: smokin g variab les, by smoking status

.Smoking status

.Variable

n

Willing

Mean (SD) n

Not willing

Mean (SD)P’�

Multivariateb

P

Former smokers

Current smokers

Age (years) at smoking initiation

Number of cigarettes/day

Years smoked

Pack-years smoked

Age (years) at smoking initiation

Number of cigarettes/day

Years smoked

Pack-years smoked

2,031

2,030

2,038

2,033

1,718

1,691

1,719

1,681

18. 1 (4.4)

19.9 (14.5)

15.5 (1 1.7)

18.7 (22.7)

18.4 (4.9)

17.1 (10.9)

19.1 (12.4)

18.9(20.8)

532

533

534

533

391

385

394

383

1 8.4 (5. 1)

16.8 (13.6)

13.7 (1 1.7)

14.4 (21.7)

18.7 (5.3)

17.2 (12.3)

18.5 (12.9)

18.7 (22.7)

0. 12

0.00

0.00

0.00

0.19

0.87

0.42

0.88

0.20

0.00

0.02

0.00

0.02

0.31

0.02

0.15

a p associated with Student’s t tests.b Derived using logistic regression, controlling for sex, age, and race (control variables categorical, as shown in Table 1).

Age started smoking (N=108)

Discrepancy in years for reported age at smoking initiation

Years smoked (Na106)

�Ji�.23-13-10-7 .6 -5 .4 .3 -2 .1 0 1 2 3 4 5 6 9 101624

Discrepancy in years for reported number of years smoked

Fig. 2. Concordance between KS waiting room questionnaire and personal interview data. Difference scores were calculated as the value reported during personal

interview minus the value reported on the waiting room questionnaire. For “years smoked” data, the values for current smokers were adjusted for time elapsed between

KS questionnaire completion and personal interview data collection.

began smoking at an earlier age and smoked a greaten numberof years than did their counterparts.

Concordance between KS Questionnaire Data and PersonalInterview Data. To date, 121 matched control subjects havebeen enrolled in the study. Of these, we had complete agree-ment between KS questionnaire data and personal interviewdata for 99% of subjects on the variable sex, 100% of subjectsfor race, 99% of subjects for date of birth, and 100% of subjectsfor smoking history (ever smoker versus never smoker). Fig. 2shows the extent of agreement for four smoking variables: agein years at smoking initiation, age in years when stoppedsmoking (former smokers), number of cigarettes smoked per

day, and the number of years smoked. For the number ofcigarettes smoked per day, the comparison was limited to

former smokers because this construct would not be consideredstatic among current smokers. Discrepancy was calculated as

the value reported during personal interview minus the valuereported on the waiting room questionnaire, and the zero values

on the graphs indicate agreement between the two methods of

data collection.

For age at smoking initiation (current and former smokers)

and age at smoking cessation (former smokers), 84 and 74%had agreement within 2 years, respectively. Among the former

smokers enrolled as a control subject, 64% had acceptablereliability in reported number of cigarettes smoked per day,with values differing by no more than five cigarettes per day.

For the reported number of years smoked among current and

former smokers, 84% had agreement within 5 years.

570 Recruiting Healthy Control Subjects

Discussion

This paper describes a successful methodology applicable to the

managed care environment that may be useful in studies re-quiring the identification of a large pool of healthy subjects.

Additionally, we contrasted characteristics of the pool of po-

tential control subjects who reported an interest in participating

in the medical research with those who requested that they not

be contacted for the purpose of research. This comparison helpscharacterize our “eligible, willing control pool” with respect to

the population of otherwise eligible subjects who presented at

a KS clinic and completed a waiting room questionnaire during

the accrual period.To attain a sufficiently large pool of eligible and willing

control subjects to enable stringent matching of case and con-

trol subjects, questionnaires are being administered to all adultspresenting at Houston-area KS clinics. To keep KS adminis-

trative personnel closely informed about the project’s progress,

we provide feedback that includes a weekly report of question-name accrual at each clinic site as well as a monthly report of

prevalence data describing the smoking patterns of their clinic

patient population. Also, a list of the names of questionnaire

respondents who indicate that they are interested in receiving

smoking cessation materials (for themselves or for others) isforwarded to the KS health promotion department; approxi-mately 20% of respondents make this request. Continuous

feedback to the KS organization is important in facilitating

successful long-term collaboration.Despite close monitoring of questionnaire accrual rates,

we experienced a temporary reduction in questionnaire accrual

rates after the initial kick-off at the KS clinics. It becameapparent that regular site visits to clinics, phone calls, and small

incentives were not enough to maintain the KS clinic person-

nd’ s interest in our project. The purpose and benefit of theproject, as well as the critical role of the KS personnel in

distributing questionnaires to patients, had not been communi-cated sufficiently at all clinics.

In month 10, we addressed this problem by hosting aluncheon at UTMDACC. Key personnel from each clinic were

invited, and the invitations were distributed by the KS director

of clinic operations. All but one KS clinic was represented atthe meeting. In preparation for the meeting, we videotaped

personnel at three clinics that had been consistently successfulin questionnaire distribution. Each of the three clinics demon-

strated the mechanism they used to distribute questionnaires at

their facilities. We anticipated that the videotapes would helpthe personnel at other clinics to generate ideas for improving

distribution at their own locations. We also videotaped theprocess used at UTMDACC to recruit lung cancer case subjectsinto the study. The results of our efforts appeared to be positive,

with response rates increasing from 791 questionnaires col-

lected in month 10 to 1495 questionnaires in month 11, an 89%

increase.

To assess possible bias in willingness to participate among

the control pool (those who completed a questionnaire), wecompared study-eligible subjects who were not interested inparticipation with those who were either willing or were unsure.Several differences were observed, but without having con-

ducted more in-depth assessments, we are not able to describereasons underlying the differences. For example, it is not clear

why female former smokers were more likely to refuse partic-ipation than male former smokers, yet there was no difference

by sex among never smokers and current smokers. Because ofthe practical limitations associated with a waiting-room ques-

tionnaire, we could not assess the multiple sociobehavioral

factors that previously have been shown to be associated with

cancer prevention behavior and participation in trials in general

(6-26). It was surprising, however, that current smokers were

least likely to refuse participation because, in general, individ-

uals interested in participating in cancer prevention research

tend to be more highly educated, have higher annual family

incomes, be regular vitamin users, and be more concerned

about getting cancer (22), characteristics not typically associ-

ated with smokers.

We were able to gain some limited information character-

izing the pool of potential control subjects who were not averse

to participation with respect to the overall sample of KS en-

rollees who completed a questionnaire. The extent to which the

characteristics of the control pool reflect the general population

of the KS patient base is not known, and our methods do not

afford the opportunity to assess the proportion of waiting room

patients who completed a questionnaire. Furthermore, it is

possible that the proportion of respondents who indicated that

they may be willing to participate and those who are matched

as controls and actually do participate, once contacted, may

differ. To date, 121 of 139 subjects (87%) contacted to serve as

a control subject have been enrolled as controls. The number of

subjects who chose not to participate when contacted (n = 18)

currently is too small to reliably assess for possible participa-

tion bias occurring at this phase of the recruitment process. In

the future, as our estimate becomes more stable, data regarding

the participation rate among contacted persons will be factored

into the overall “willingness to participate” rates. In comparing

the waiting room questionnaire data with personal interview

data collected from the enrolled control subjects, we observed

high levels of agreement for sociodemographic factors and

reports of ever smoking. In contrast, there was some variation

in reports of age of smoking initiation and smoking cessation,

number of years smoked, and number of cigarettes smoked per

day. When the interview data are unacceptably discrepant from

the KS questionnaire data, hence voiding the “match,” we

reselect another matched control subject. The original control is

kept for future matching to a case.

It is important to reinforce that because the cases do not

derive from defined populations, the case-control studies de-

scribed here are not population based. Consequently, compa-

rability of the two base populations cannot be assumed, and

there are inherent limitations associated with our methods of

subject selection (2, 3). This potential bias is less problematic,

however, when the study hypotheses are focused on genetic

susceptibility factors as opposed to lifestyle- or exposure-de-

pendent factors.

In summary, it is our experience that although the appro-

priateness of the population may be controversial for some

studies, developing a collaborative agreement with a large

managed care organization offers a feasible and workable

mechanism through which investigators can identify and access

large numbers of healthy persons of diverse ethnicities and

socioeconomic backgrounds who are interested in participating

in medical research. Once established, the pool becomes a

valuable resource for the selection of healthy subjects for both

case-control and cohort studies. Because the number of molec-

ular epidemiological case-control studies is growing rapidly,

studies of perceived benefits and barriers of participation, as

well as factors associated with willingness to participate in

these types of studies, would be worthy contributions to the

literature.

Cancer Epidemiokaj�, Biomarkers & Prevention 571

Acknowledgments

We thank Joanne Sider for questionnaire formatting and development, Betty

Henry and Pat Pillow for data inspection and cleaning, Mary Harris and SecnobiaEaster for data entry, and Pain Porter and Mary McCabe for conducting panic-

ipant interviews. We also thank all KS Foundation personnel who have made this

project possible, including Terry Litchfield, Fran Greene, Cynthia Sustaita, andthe clinic personnel.

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