Evaluating Candidate Principal Surrogate Endpoints
Evaluating Candidate Principal Surrogate Endpoints
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DOI：
10.1111/j.1541-0420.2008.01014.x
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发表时间：
2008-12-01
期刊：
影响因子：
1.9
通讯作者：
Hudgens, Michael G.
中科院分区：
文献类型：
--
作者：
Gilbert, Peter B.;Hudgens, Michael G.
Frangakis和Rubin（2002，Biometrics 58，21-29）提出了基于因果效应的替代终点（“主要”替代）的新定义。我们引入了一个被估量来评估一个主要的替代物，因果效应预测性（CEP）表面，它量化了因果治疗对生物标志物的影响如何预测因果治疗对临床终点的影响。尽管CEP表面由于缺失潜在结果而无法识别，但可以通过纳入预测生物标志物的基线协变量来识别。鉴于在一个大型盲法随机临床试验中对这种基线预测因子和生物标志物进行病例队列抽样，我们开发了一种估计CEP表面的估计似然方法。该估计评估了生物标志物的“替代值”，用于可靠地预测与试验相同或相似设置的临床治疗效果。CEP曲面图提供了一种比较多种生物标志物的替代值的方法。该方法说明了评估作为感染的替代终点的疫苗的免疫反应的问题。
Frangakis and Rubin (2002, Biometrics 58, 21-29) proposed a new definition of a surrogate end-point (a "principal" surrogate) based on causal effects. We introduce an estimand for evaluating a principal surrogate, the causal effect predictiveness (CEP) surface, which quantifies how well causal treatment effects on the biomarker predict causal treatment effects on the clinical endpoint. Although the CEP surface is not identifiable due to missing potential outcomes, it can be identified by incorporating a baseline covariate(s) that predicts the biomarker. Given case-cohort sampling of such a baseline predictor and the biomarker in a large blinded randomized clinical trial, we develop an estimated likelihood method for estimating the CEP surface. This estimation assesses the "surrogate value" of the biomarker for reliably predicting clinical treatment effects for the same or similar setting as the trial. A CEP surface plot provides a way to compare the surrogate value of multiple biomarkers. The approach is illustrated by the problem of assessing an immune response to a vaccine as a surrogate endpoint for infection.