Assessment of heterogeneity in an individual participant data meta-analysis of prediction models: An overview and illustration
Assessment of heterogeneity in an individual participant data meta-analysis of prediction models: An overview and illustration
复制标题
DOI：
10.1002/sim.8296
复制
发表时间：
2019-08-02
影响因子：
2
通讯作者：
van Houwelingen, Hans C.
中科院分区：
文献类型：
--
作者：
Steyerberg, Ewout W.;Nieboer, Daan;van Houwelingen, Hans C.
临床预测模型旨在提供诊断或预后终点的绝对风险估计。这些模型可以从元分析背景下的各种研究数据中得出。我们描述并提出了评估预测器效应和基于不同来源数据的模型所产生的预测的异质性的方法。这些方法在一项创伤性脑损伤患者的案例研究中得到了说明，我们的目标是利用荟萃分析技术预测基于个体患者数据的6个月死亡率（15项研究，n = 11022例患者）。对异质性各个方面的洞察对于开发更好的模型和理解绝对风险预测的可移植性问题非常重要。
Clinical prediction models aim to provide estimates of absolute risk for a diagnostic or prognostic endpoint. Such models may be derived from data from various studies in the context of a meta-analysis. We describe and propose approaches for assessing heterogeneity in predictor effects and predictions arising from models based on data from different sources. These methods are illustrated in a case study with patients suffering from traumatic brain injury, where we aim to predict 6-month mortality based on individual patient data using meta-analytic techniques (15 studies, n = 11 022 patients). The insights into various aspects of heterogeneity are important to develop better models and understand problems with the transportability of absolute risk predictions.