Department of Statistics and Data Science, The University of Texas at Austin, Austin, TX.
Department of Biomedical Data Science, Stanford University, Stanford, CA.
Med Care. 2024 Feb 1;62(2):102-108. doi: 10.1097/MLR.0000000000001956. Epub 2023 Dec 11.
There is tremendous interest in evaluating surrogate markers given their potential to decrease study time, costs, and patient burden.
The purpose of this statistical workshop article is to describe and illustrate how to evaluate a surrogate marker of interest using the proportion of treatment effect (PTE) explained as a measure of the quality of the surrogate marker for: (1) a setting with a general fully observed primary outcome (eg, biopsy score); and (2) a setting with a time-to-event primary outcome which may be censored due to study termination or early drop out (eg, time to diabetes).
The methods are motivated by 2 randomized trials, one among children with nonalcoholic fatty liver disease where the primary outcome was a change in biopsy score (general outcome) and another study among adults at high risk for Type 2 diabetes where the primary outcome was time to diabetes (time-to-event outcome). The methods are illustrated using the Rsurrogate package with a detailed R code provided.
In the biopsy score outcome setting, the estimated PTE of the examined surrogate marker was 0.182 (95% confidence interval [CI]: 0.121, 0.240), that is, the surrogate explained only 18.2% of the treatment effect on the biopsy score. In the diabetes setting, the estimated PTE of the surrogate marker was 0.596 (95% CI: 0.404, 0.760), that is, the surrogate explained 59.6% of the treatment effect on diabetes incidence.
This statistical workshop provides tools that will support future researchers in the evaluation of surrogate markers.
由于替代标志物具有降低研究时间、成本和患者负担的潜力，因此人们对其评价非常感兴趣。
本统计研讨会文章的目的是描述和说明如何使用治疗效果比例（PTE）来评估感兴趣的替代标志物，作为替代标志物质量的衡量标准：（1）具有一般完全观察主要结局（例如，活检评分）的设置；（2）具有因研究终止或早期退出而可能被删失的时间事件主要结局（例如，糖尿病时间）的设置。
该方法源于两项随机试验，一项是针对非酒精性脂肪性肝病儿童的研究，主要结局是活检评分的变化（一般结局），另一项是针对 2 型糖尿病高危成人的研究，主要结局是糖尿病的时间（时间到事件结局）。该方法使用 Rsurrogate 包进行说明，并提供了详细的 R 代码。
在活检评分结局设置中，所检查替代标志物的估计 PTE 为 0.182（95%置信区间[CI]：0.121，0.240），即替代标志物仅解释了活检评分治疗效果的 18.2%。在糖尿病设置中，替代标志物的估计 PTE 为 0.596（95%置信区间[CI]：0.404，0.760），即替代标志物解释了糖尿病发生率治疗效果的 59.6%。
本统计研讨会提供了工具，将支持未来研究人员对替代标志物的评价。
