Estimating time-varying treatment switching effects via local linear smoothing and quasi-likelihood

Abstract

Vascular access complications have been the major cause of excessive morbidity and mortality in the dialysis population. They also account for a large portion of hospitalization for dialysis patients and are a main contributor to the high dialysis care cost. Despite the Fistula First Initiative, the majority of patients initiate dialysis with a central venous catheter which is associated with poor outcomes. In this paper we investigate whether switching from a central venous catheter to an arteriovenous fistula sooner is associated with smaller hospitalization rate. We propose a flexible model for time-varying switching effect while accounting for trend over calendar time, trend over time on dialysis and time-varying effects of covariates. We model all unknown functions nonparametrically using local linear smoothers and estimate them using weighted local quasi-likelihood. We show that the proposed estimators have the desirable large-sample properties and excellent performance in simulations. Application of the proposed method to a real data set indicates that hospitalization rate is smaller when patients switch from a central venous catheter to an arteriovenous fistula sooner. The proposed methods are general which are applicable to other situations with treatment switching.