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J Natl Cancer Inst Monogr. 2010;2010(40):97-103. doi: 10.1093/jncimonographs/lgq011.

Intraclass correlation estimates for cancer screening outcomes: estimates and applications in the design of group-randomized cancer screening studies.

Author information

  • 1Center for Biostatistics, The Ohio State University, 2012 Kenny Rd, Columbus, OH 43221, USA. erinn.hade@osumc.edu

Erratum in

  • J Natl Cancer Inst Monogr. 2010;2010(41):223.
  • J Natl Cancer Inst Monogr. 2011;2011(43):152.

Abstract

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.

PMID:
20386058
[PubMed - indexed for MEDLINE]
PMCID:
PMC2924625
Free PMC Article
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