The Annals of Applied Statistics
- Ann. Appl. Stat.
- Volume 11, Number 3 (2017), 1763-1786.
Doubly robust estimation of optimal treatment regimes for survival data—with application to an HIV/AIDS study
In many biomedical settings, assigning every patient the same treatment may not be optimal due to patient heterogeneity. Individualized treatment regimes have the potential to dramatically improve clinical outcomes. When the primary outcome is censored survival time, a main interest is to find optimal treatment regimes that maximize the survival probability of patients. Since the survival curve is a function of time, it is important to balance short-term and long-term benefit when assigning treatments. In this paper, we propose a doubly robust approach to estimate optimal treatment regimes that optimize a user specified function of the survival curve, including the restricted mean survival time and the median survival time. The empirical and asymptotic properties of the proposed method are investigated. The proposed method is applied to a data set from an ongoing HIV/AIDS clinical observational study conducted by the University of North Carolina (UNC) Center of AIDS Research (CFAR), and shows the proposed methods significantly improve the restricted mean time of the initial treatment duration. Finally, the proposed methods are extended to multi-stage studies.
Ann. Appl. Stat., Volume 11, Number 3 (2017), 1763-1786.
Received: February 2016
Revised: March 2017
First available in Project Euclid: 5 October 2017
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Jiang, Runchao; Lu, Wenbin; Song, Rui; Hudgens, Michael G.; Naprvavnik, Sonia. Doubly robust estimation of optimal treatment regimes for survival data—with application to an HIV/AIDS study. Ann. Appl. Stat. 11 (2017), no. 3, 1763--1786. doi:10.1214/17-AOAS1057. https://projecteuclid.org/euclid.aoas/1507168847
- Supplement to “Doubly robust estimation of optimal treatment regimes for survival data—with application to an HIV/AIDS study”. It contains regularity conditions referenced in Theorems 1 and 2, and additional simulation results referenced in Sections 4 and 6.