Individual participant data meta-analysis of prognosis studies

R. Riley, T. Debray, K. Moons
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Abstract

An alternative approach to meta-analysis of aggregate data from published prognosis research (as addressed in Chapter 9), with its challenges of heterogeneity and lack of information, is to conduct meta-analysis of individual participant data (IPD), that is, the original raw data of the individuals who are included in the primary prognosis studies. The approach is increasingly feasible as data sharing and open-access data become more popular, and the chapter highlights why they offer enormous advantages for a robust and meaningful evidence synthesis of prognosis studies. In particular, better prognostic models can be developed and directly validated across multiple settings, and power is increased to detect genuine predictors of treatment response. Key steps in such an IPD meta-analysis are explained, including practical guidance on how to obtain, handle, and synthesize data, and what potential challenges may be encountered.
预后研究的个体参与者数据荟萃分析
对已发表的预后研究(如第9章所述)的汇总数据进行荟萃分析的另一种方法是对个体参与者数据(IPD)进行荟萃分析,即纳入初级预后研究的个体的原始原始数据。该方法存在异质性和信息缺乏的挑战。随着数据共享和开放获取数据变得越来越流行,这种方法越来越可行,本章强调了为什么它们为预后研究的可靠和有意义的证据综合提供了巨大的优势。特别是,可以开发更好的预后模型并在多种情况下直接验证,并且增加了检测治疗反应的真正预测因子的能力。解释了这种IPD元分析的关键步骤,包括如何获取、处理和综合数据的实际指导,以及可能遇到的潜在挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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