Adjusting for time-varying confounders in survival analysis using structural nested cumulative survival time models.

ABSTRACT: Accounting for time-varying confounding when assessing the causal effects of time-varying exposures on survival time is challenging. Standard survival methods that incorporate time-varying confounders as covariates generally yield biased effect estimates. Estimators using weighting by inverse probability of exposure can be unstable when confounders are highly predictive of exposure or the exposure is continuous. Structural nested accelerated failure time models (AFTMs) require artificial recensoring, which can cause estimation difficulties. Here, we introduce the structural nested cumulative survival time model (SNCSTM). This model assumes that intervening to set exposure at time t to zero has an additive effect on the subsequent conditional hazard given exposure and confounder histories w

SUBMITTER: Seaman S 

PROVIDER: S-EPMC7317577 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature