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This paper provides guidance for researchers with some mathematicalbackground on the conduct of time-to-event analysis in observational studiesbased on intensity (hazard) models. Discussions of basic concepts like timeaxis, event definition and censoring are given. Hazard models are introduced,with special emphasis on the Cox proportional hazards regression model. Weprovide check lists that may be useful both when fitting the model andassessing its goodness of fit and when interpreting the results. Specialattention is paid to how to avoid problems with immortal time bias byintroducing time-dependent covariates. We discuss prediction based on hazardmodels and difficulties when attempting to draw proper causal conclusions fromsuch models. Finally, we present a series of examples where the methods andcheck lists are exemplified. Computational details and implementation using thefreely available R software are documented in Supplementary Material. The paperwas prepared as part of the STRATOS initiative.

Analysis of time-to-event for observational studies: Guidance to the use of intensity models