A Sequential Stratification Method for Estimating the Effect of a Time‐Dependent Experimental Treatment in Observational Studies

Summary Survival analysis is often used to compare experimental and conventional treatments. In observational studies, the therapy may change during follow‐up and such crossovers can be summarized by time‐dependent covariates. Given the ever‐increasing donor organ shortage, higher‐risk kidneys from expanded criterion donors (ECD) are being transplanted. Transplant candidates can choose whether to accept an ECD organ (experimental therapy), or to remain on dialysis and wait for a possible non‐ECD transplant later (conventional therapy). A three‐group time‐dependent analysis of such data involves estimating parameters corresponding to two time‐dependent indicator covariates representing ECD transplant and non‐ECD transplant, each compared to remaining on dialysis on the waitlist. However, the ECD hazard ratio estimated by this time‐dependent analysis fails to account for the fact that patients who forego an ECD transplant are not destined to remain on dialysis forever, but could subsequently receive a non‐ECD transplant. We propose a novel method of estimating the survival benefit of ECD transplantation relative to conventional therapy (waitlist with possible subsequent non‐ECD transplant). Compared to the time‐dependent analysis, the proposed method more accurately characterizes the data structure and yields a more direct estimate of the relative outcome with an ECD transplant.