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A0557
Title: Doubly robust estimator for net survival rate in analyses of cancer registry data Authors:  Satoshi Hattori - Osaka University (Japan) [presenting]
Abstract: Cancer population studies based on cancer registry databases are widely conducted to address various research questions. In general, cancer registry databases do not collect information on cause of death. The net survival rate is defined as the survival rate if a subject would not die for any causes other than cancer. This counterfactual concept is widely used for the analyses of cancer registry data. Almost all the statistical methods for cancer registry data assume independent censoring. However, in practice of cancer registry analyses, covariate-dependent censoring frequently arises and existing methods allowing the covariate-dependent censoring rely on correct regression modelling of censoring time or that of the net survival. We propose a new estimator for survival time, which is shown to be doubly robust in the sense that it is consistent at least one of the regression models for survival time and for censoring time. We examine the theoretical and empirical properties of our proposed estimator by asymptotic theory and simulation studies. We also apply the proposed method to cancer registry data for gastric cancer patients in Osaka, Japan.