RESEARCH ARTICLE Open Access Estimating time-varying exposure-outcome associations using case-control data: logistic and case-cohort analyses Ruth H. Keogh 1* , Punam Mangtani 2 , Laura Rodrigues 2 and Patrick Nguipdop Djomo 2 Abstract Background: Traditional analyses of standard case-control studies using logistic regression do not allow estimation of time-varying associations between exposures and the outcome. We present two approaches which allow this. The motivation is a study of vaccine efficacy as a function of time since vaccination. Methods: Our first approach is to estimate time-varying exposure-outcome associations by fitting a series of logistic regressions within successive time periods, reusing controls across periods. Our second approach treats the case- control sample as a case-cohort study, with the controls forming the subcohort. In the case-cohort analysis, controls contribute information at all times they are at risk. Extensions allow left truncation, frequency matching and, using the case-cohort analysis, time-varying exposures. Simulations are used to investigate the methods. Results: The simulation results show that both methods give correct estimates of time-varying effects of exposures using standard case-control data. Using the logistic approach there are efficiency gains by reusing controls over time and care should be taken over the definition of controls within time periods. However, using the case-cohort analysis there is no ambiguity over the definition of controls. The performance of the two analyses is very similar when controls are used most efficiently under the logistic approach. Conclusions: Using our methods, case-control studies can be used to estimate time-varying exposure-outcome associations where they may not previously have been considered. The case-cohort analysis has several advantages, including that it allows estimation of time-varying associations as a continuous function of time, while the logistic regression approach is restricted to assuming a step function form for the time-varying association. Keywords: Case-control study, Case-cohort study, Cox proportional hazards model, Logistic regression, Time- varying association, Vaccine efficacy Background Case-control studies are widely used to study associa- tions between exposures and disease (or other) out- comes, especially when the outcome is rare. For overviews see Breslow and Day (1980) , Breslow (1996)  and Keogh and Cox (2014) . In a ‘ standard ’ case-control study cases are individuals who experienced the outcome of interest within a specified time period and controls are chosen to represent the non-cases in the same population. In this paper we describe methods for estimating time- varying associations between exposures and outcomes using standard case-control study data, focusing on unmatched and frequency matched studies. Conven- tional analyses of case-control data using logistic regres- sion do not accommodate time-varying associations. We outline two approaches. One is to estimate associations
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- Spring '19
- Cohort study, Study design, Proportional hazards models, Keogh