Abstract
When carefully planned and analysed, the case-cohort design is a powerful choice for follow-up studies with multiple event types of interest. While the literature is rich with analysis methods for case-cohort data, little is written about the designing of a case-cohort study. Our experiences in designing, coordinating and analysing the MORGAM case-cohort study are potentially useful for other studies with similar characteristics. The motivation for using the case-cohort design in the MORGAM genetic study is discussed and issues relevant to its planning and analysis are studied. We propose solutions for appending the earlier case-cohort selection after an extension of the follow-up period and for achieving maximum overlap between earlier designs and the case-cohort design. Approaches for statistical analysis are studied in a simulation example based on the MORGAM data.
Highlights
The MORGAM (MONICA, Risk, Genetics, Archiving, and Monograph) Project is an ongoing multinational collaborative study with the overall aim of studying a limited number of well-defined phenotypes and several hundred genetic factors by pooling data from cohorts defined in MONICA (Multinational MONItoring of trends and determinants in CArdiovascular disease) and other similar cross-sectional risk factor surveys [1,2]
This paper describes the case-cohort design of the MORGAM Project in detail and discusses analysis approaches for case-cohort data with the intention of providing proper guidelines which would be helpful in designing studies with similar characteristics
The cost-effectiveness and the availability of software for the analysis make the case-cohort design appealing among epidemiologists
Summary
The MORGAM (MONICA, Risk, Genetics, Archiving, and Monograph) Project is an ongoing multinational collaborative study with the overall aim of studying a limited number of well-defined phenotypes and several hundred genetic factors by pooling data from cohorts defined in MONICA (Multinational MONItoring of trends and determinants in CArdiovascular disease) and other similar cross-sectional risk factor surveys [1,2]. In addition to the pseudolikelihood based time-to-event analysis, some authors have recently considered a full likelihood approach where the cohort sampling design is handled as a missing data problem. In this approach the likelihood expression is constructed for the complete cohort instead of the case-cohort set. This paper describes the case-cohort design of the MORGAM Project in detail and discusses analysis approaches for case-cohort data with the intention of providing proper guidelines which would be helpful in designing studies with similar characteristics. We describe the procedure used in selecting the subcohort in the MORGAM case-cohort design and approaches to statistical analysis of the casecohort data. Various aspects of the case-cohort design are illustrated using a single MORGAM cohort
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