Jiang Runchao, Lu Wenbin, Song Rui, Hudgens Michael G, Naprvavnik Sonia
Department of Statistics, North Carolina State University Raleigh, North Carolina, USA.
Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Ann Appl Stat. 2017 Sep;11(3):1763-1786. doi: 10.1214/17-AOAS1057. Epub 2017 Oct 5.
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.
在许多生物医学场景中，由于患者的异质性，对每个患者采用相同的治疗方法可能并非最佳选择。个体化治疗方案有可能显著改善临床结果。当主要结局是删失生存时间时，一个主要关注点是找到能使患者生存概率最大化的最佳治疗方案。由于生存曲线是时间的函数，在分配治疗时平衡短期和长期益处很重要。在本文中，我们提出一种双重稳健的方法来估计最佳治疗方案，该方案能优化用户指定的生存曲线函数，包括受限平均生存时间和中位生存时间。我们研究了所提方法的经验性质和渐近性质。所提方法应用于北卡罗来纳大学（UNC）艾滋病研究中心（CFAR）正在进行的一项HIV/AIDS临床观察性研究的数据集，结果表明所提方法显著改善了初始治疗持续时间的受限平均时间。最后，我们将所提方法扩展到多阶段研究。
