Burzykowski Tomasz, Buyse Marc
Center for Statistics, Hasselt University, Agoralaan (bldg. D), B3590 Diepenbeek, Belgium.
Pharm Stat. 2006 Jul-Sep;5(3):173-86. doi: 10.1002/pst.207.
In many therapeutic areas, the identification and validation of surrogate endpoints is of prime interest to reduce the duration and/or size of clinical trials. Buyse et al. [Biostatistics 2000; 1:49-67] proposed a meta-analytic approach to the validation. In this approach, the validity of a surrogate is quantified by the coefficient of determination Rtrial2 obtained from a model, which allows for prediction of the treatment effect on the endpoint of interest ('true' endpoint) from the effect on the surrogate. One problem related to the use of Rtial2 is the difficulty in interpreting its value. To address this difficulty, in this paper we introduce a new concept, the so-called surrogate threshold effect (STE), defined as the minimum treatment effect on the surrogate necessary to predict a non-zero effect on the true endpoint. One of its interesting features, apart from providing information relevant to the practical use of a surrogate endpoint, is its natural interpretation from a clinical point of view.
在许多治疗领域，识别和验证替代终点对于缩短临床试验的持续时间和/或规模至关重要。比瑟等人[《生物统计学》2000年；1:49 - 67]提出了一种用于验证的荟萃分析方法。在这种方法中，替代指标的有效性通过从一个模型中获得的决定系数(R_{trial}^2)来量化，该模型允许根据对替代指标的效应预测对感兴趣的终点（“真实”终点）的治疗效应。与使用(R_{trial}^2)相关的一个问题是难以解释其值。为了解决这个难题，在本文中我们引入了一个新概念，即所谓的替代阈值效应（STE），定义为预测对真实终点有非零效应所需的对替代指标的最小治疗效应。除了提供与替代终点实际应用相关的信息外，它的一个有趣特征是从临床角度有自然的解释。
