Intraclass correlation estimates for cancer screening outcomes: estimates and applications in the design of group-randomized cancer screening studies.
BACKGROUND
Screening has become one of our best tools for early detection and prevention of cancer. The group-randomized trial is the most rigorous experimental design for evaluating multilevel interventions. However, identifying the proper sample size for a group-randomized trial requires reliable estimates of intraclass correlation (ICC) for screening outcomes, which are not available to researchers. We present crude and adjusted ICC estimates for cancer screening outcomes for various levels of aggregation (physician, clinic, and county) and provide an example of how these ICC estimates may be used in the design of a future trial.


METHODS
Investigators working in the area of cancer screening were contacted and asked to provide crude and adjusted ICC estimates using the analysis of variance method estimator.


RESULTS
Of the 29 investigators identified, estimates were obtained from 10 investigators who had relevant data. ICC estimates were calculated from 13 different studies, with more than half of the studies collecting information on colorectal screening. In the majority of cases, ICC estimates could be adjusted for age, education, and other demographic characteristics, leading to a reduction in the ICC. ICC estimates varied considerably by cancer site and level of aggregation of the groups.


CONCLUSIONS
Previously, only two articles had published ICCs for cancer screening outcomes. We have complied more than 130 crude and adjusted ICC estimates covering breast, cervical, colon, and prostate screening and have detailed them by level of aggregation, screening measure, and study characteristics. We have also demonstrated their use in planning a future trial and the need for the evaluation of the proposed interval estimator for binary outcomes under conditions typically seen in GRTs.
Hade
Erinn M
EM
Center for Biostatistics, The Ohio State University, 2012 Kenny Rd, Columbus, OH 43221, USA. erinn.hade@osumc.edu
Murray
David M
DM
Pennell
Michael L
ML
Rhoda
Dale
D
Paskett
Electra D
ED
Champion
Victoria L
VL
Crabtree
Benjamin F
BF
Dietrich
Allen
A
Dignan
Mark B
MB
Farmer
Melissa
M
Fenton
Joshua J
JJ
Flocke
Susan
S
Hiatt
Robert A
RA
Hudson
Shawna V
SV
Mitchell
Michael
M
Monahan
Patrick
P
Shariff-Marco
Salma
S
Slone
Stacey L
SL
Stange
Kurt
K
Stewart
Susan L
SL
Strickland
Pamela A Ohman
PA
D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D001943:Breast Neoplasms / Q000175:diagnosis; D015179:Colorectal Neoplasms / Q000175:diagnosis; D003625:Data Collection; D055088:Early Detection of Cancer / Q000706:statistics & numerical data*; D016099:Endoscopy, Gastrointestinal / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D008297:Male; D008327:Mammography / Q000706:statistics & numerical data; D008403:Mass Screening / Q000458:organization & administration / Q000592:standards*; D008875:Middle Aged; D009780:Occult Blood; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D017430:Prostate-Specific Antigen / Q000097:blood; D011471:Prostatic Neoplasms / Q000175:diagnosis; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D012107:Research Design; D018401:Sample Size; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis* / Q000453:epidemiology; D014626:Vaginal Smears / Q000706:statistics & numerical data
D017430:Prostate-Specific Antigen
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