Analysis of secondary outcomes in nested case-control study designs

One of the main perceived advantages of using a case-cohort design compared with a nested case-control design in an epidemiologic study is the ability to evaluate with the same subcohort outcomes other than the primary outcome of interest. In this paper, we show that valid inferences about secondary outcomes can also be achieved in nested case-control studies by using the inclusion probability weighting method in combination with an approximate jackknife standard error that can be computed using existing software. Simulation studies demonstrate that when the sample size is sufficient, this approach yields valid type 1 error and coverage rates for the analysis of secondary outcomes in nested case-control designs. Interestingly, the statistical power of the nested case-control design was comparable with that of the case-cohort design when the primary and secondary outcomes were positively correlated. The proposed method is illustrated with the data from a cohort in Cardiovascular Health Study to study the association of C-reactive protein levels and the incidence of congestive heart failure.