Estimating the average treatment effect on survival based on observational data and using partly conditional modeling.

ABSTRACT: Treatments are frequently evaluated in terms of their effect on patient survival. In settings where randomization of treatment is not feasible, observational data are employed, necessitating correction for covariate imbalances. Treatments are usually compared using a hazard ratio. Most existing methods which quantify the treatment effect through the survival function are applicable to treatments assigned at time 0. In the data structure of our interest, subjects typically begin follow-up untreated; time-until-treatment, and the pretreatment death hazard are both heavily influenced by longitudinal covariates; and subjects may experience periods of treatment ineligibility. We propose semiparametric methods for estimating the average difference in restricted mean survival time attributable to

SUBMITTER: Gong Q 

PROVIDER: S-EPMC5116003 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature