Analysis of randomized comparative clinical trial data for personalized treatment selections
Analysis of randomized comparative clinical trial data for personalized treatment selections
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DOI：
10.1093/biostatistics/kxq060
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发表时间：
2011-04-01
期刊：
影响因子：
2.1
通讯作者：
Wei, L. J.
中科院分区：
文献类型：
--
作者：
Cai, Tianxi;Tian, Lu;Wei, L. J.
假设在常规随机临床试验环境下，将新疗法与标准疗法进行比较。在这篇文章中，我们提出了一个系统的，2阶段的估计程序的受试者水平的治疗差异，为未来患者的疾病管理和治疗选择。为了构建这个程序，我们首先利用参数或半参数方法来估计个体水平的治疗差异，并使用这些估计来创建一个指数评分系统，用于对患者进行分组。然后，我们通过非参数函数估计方法一致地估计每个受试者亚组的平均治疗差异。此外，构建逐点和同步区间估计值，以推断此类亚组特异性治疗差异。新的建议是说明与临床试验的数据，用于评估的疗效和毒性的3种药物组合与标准的2种药物组合治疗HIV-1感染的患者。
Suppose that under the conventional randomized clinical trial setting, a new therapy is compared with a standard treatment. In this article, we propose a systematic, 2-stage estimation procedure for the subject-level treatment differences for future patient's disease management and treatment selections. To construct this procedure, we first utilize a parametric or semiparametric method to estimate individual-level treatment differences, and use these estimates to create an index scoring system for grouping patients. We then consistently estimate the average treatment difference for each subgroup of subjects via a nonparametric function estimation method. Furthermore, pointwise and simultaneous interval estimates are constructed to make inferences about such subgroup-specific treatment differences. The new proposal is illustrated with the data from a clinical trial for evaluating the efficacy and toxicity of a 3-drug combination versus a standard 2-drug combination for treating HIV-1-infected patients.