Adjusting for observational secondary treatments in estimating the effects of randomized treatments

Biostatistics: 1/24/13

In randomized clinical trials, for example, on cancer patients, it is not uncommon that patients may voluntarily initiate a secondary treatment postrandomization, which needs to be properly adjusted for in estimating the “true” effects of randomized treatments. As an alternative to the approach based on a marginal structural Cox model (MSCM) in Zhang and Wang [(2012). Estimating treatment effects from a randomized trial in the presence of a secondary treatment. Biostatistics 13, 625–636], we propose methods that treat the time to start a secondary treatment as a dependent censoring process, which is handled separately from the usual censoring such as the loss to follow-up. Read more