Mediation analyses have been implemented in observational studies such as crosssectional, case-control and both prospective and retrospective cohort studies. However, little has been done for mediation analysis in a case-control study with subsequently collected (secondary and/or tertiary) outcomes. This may happen in a case-control study with additional interests of a secondary/tertiary outcome and direct or indirect effects of exposure on the secondary (tertiary) outcome through the primary (secondary) outcome. Performing such mediation analysis ignoring the complex study design could lead to seriously biased estimates since the primary case-control sample was a biased sample. To address this, we propose to account for the sampling process with the ratio-of-mediator-probability weighting method and establishedtwo new weighting estimators. The proposed estimators work well with marginal structural models in estimating controlled direct effects, natural direct effects and natural indirect effects under complex study designs and allow for the existence of exposure-mediator interaction in relation to the outcome. We compare the proposed methods with existing and extended versions of existing methods and find that the proposed methods significantly reduce the computational resources when estimating standard errors compared to existing methods. We also illustrate the implementation of the proposed weighting estimators using real-world data. Finally, we explore the minimum detectable effect sizes and the optimal case-to-control ratio for proposed weighting estimators for case-control studies with secondary (tertiary) outcomes.
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