Combescure C, Daures J P, Foucher Y
Division of Clinical Epidemiology, University Hospital of Geneva, Geneva, Switzerland Center of Clinical Research, University of Geneva, Switzerland.
Department of Biostatistics, Institut Universitaire de Recherche Clinique, France.
Stat Methods Med Res. 2016 Apr;25(2):674-85. doi: 10.1177/0962280212464542. Epub 2012 Nov 1.
Meta-analyses are popular tools to summarize the results of publications. Prognostic performances of a marker are usually summarized by meta-analyses of survival curves or hazard ratios. These approaches may detect a difference in survival according to the marker but do not allow evaluation of its prognostic capacity. Time-dependent receiver operating characteristic curves evaluate the ability of a marker to predict time-to-event. In this article, we describe an adaptation of time-dependent summary receiver operating characteristic curves from published survival curves. To achieve this goal, we modeled the marker and the time-to-event distributions using non-linear mixed models. First, we applied this methodology to individual data in kidney transplantation presented as aggregated data, in order to validate the method. Second, we re-analyzed a published meta-analysis, which focused on the capacity of KI-67 to predict the overall survival of patients with breast cancer.
荟萃分析是总结出版物结果的常用工具。标志物的预后表现通常通过生存曲线或风险比的荟萃分析来总结。这些方法可能会根据标志物检测出生存差异，但无法评估其预后能力。时间依赖性受试者工作特征曲线评估标志物预测事件发生时间的能力。在本文中，我们描述了一种根据已发表的生存曲线对时间依赖性汇总受试者工作特征曲线进行的改编。为实现这一目标，我们使用非线性混合模型对标志物和事件发生时间分布进行建模。首先，我们将这种方法应用于以汇总数据形式呈现的肾移植个体数据，以验证该方法。其次，我们重新分析了一项已发表的荟萃分析，该分析聚焦于 Ki-67 预测乳腺癌患者总生存的能力。
