研究动态
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替代终点元回归:对监管者和试验者有用的统计数据。

Surrogate endpoint meta-regression: Useful statistics for regulators and trialists.

发表日期:2024 Aug 31
作者: Stuart G Baker, Marissa N D Lassere, Wang Pok Lo
来源: JOURNAL OF CLINICAL EPIDEMIOLOGY

摘要:

使用替代终点的主要目的是比使用真实终点更快地估计对真实终点的治疗效果。基于具有替代终点和真实终点的历史随机试验的元回归,我们讨论了应用和评估替代终点的统计数据。我们根据试验级数据的两种类型的线性元回归计算了统计数据:简单随机效应和新颖随机效应与超过 2 个组的试验中估计治疗效果之间的相关性。一个关键的统计数据是元回归线的估计截距。由于与单一因果途径的一致性以及将治疗标记为对照的不变性,在推断新治疗时,较小或不具有统计显着性的截距会增加置信度。对于将元回归应用于新治疗的监管者来说,一个有用的统计数据是 95% 的预测区间。对于计划试验新治疗方法的临床试验人员来说,有用的统计数据是替代阈值效应比例、根据退出调整的样本量乘数以及新颖的真实终点优势。我们用涉及抗高血压的替代终点元回归来说明这些统计数据治疗、乳腺癌筛查和结直肠癌治疗。监管机构和试验者在应用和评估替代终点时应考虑使用这些统计数据。由爱思唯尔公司发布。
The main purpose of using a surrogate endpoint is to estimate the treatment effect on the true endpoint sooner than with a true endpoint. Based on a meta-regression of historical randomized trials with surrogate and true endpoints, we discuss statistics for applying and evaluating surrogate endpoints.We computed statistics from two types of linear meta-regressions for trial-level data: simple random effects and novel random effects with correlations among estimated treatment effects in trials with more than 2 arms. A key statistic is the estimated intercept of the meta-regression line. An intercept that is small or not statistically significant increases confidence when extrapolating to a new treatment because of consistency with a single causal pathway and invariance to labeling of treatments as controls. For a regulator applying the meta-regression to a new treatment, a useful statistic is the 95% prediction interval. For a clinical trialist planning a trial of a new treatment, useful statistics are the surrogate threshold effect proportion, the sample size multiplier adjusted for dropouts, and the novel true endpoint advantage.We illustrate these statistics with surrogate endpoint meta-regressions involving anti-hypertension treatment, breast cancer screening, and colorectal cancer treatment.Regulators and trialists should consider using these statistics when applying and evaluating surrogate endpoints.Published by Elsevier Inc.