Am J Epidemiol. 2022 Mar 24;191(5):948-956. doi: 10.1093/aje/kwac013.
Clinicians frequently must decide whether a patient's measurement reflects that of a healthy "normal" individual. Thus, the reference range is defined as the interval in which some proportion (frequently 95%) of measurements from a healthy population is expected to fall. One can estimate it from a single study or preferably from a meta-analysis of multiple studies to increase generalizability. This range differs from the confidence interval for the pooled mean and the prediction interval for a new study mean in a meta-analysis, which do not capture natural variation across healthy individuals. Methods for estimating the reference range from a meta-analysis of aggregate data that incorporates both within- and between-study variations were recently proposed. In this guide, we present 3 approaches for estimating the reference range: one frequentist, one Bayesian, and one empirical. Each method can be applied to either aggregate or individual-participant data meta-analysis, with the latter being the gold standard when available. We illustrate the application of these approaches to data from a previously published individual-participant data meta-analysis of studies measuring liver stiffness by transient elastography in healthy individuals between 2006 and 2016.
临床医生经常需要确定患者的测量值是否反映了健康“正常”个体的情况。因此,参考范围被定义为健康人群中某些比例(通常为 95%)的测量值所预期的区间。可以从单一研究中进行估计,或者最好从多个研究的荟萃分析中进行估计,以提高其普遍性。该范围与荟萃分析中汇总均值的置信区间和新研究均值的预测区间不同,后两者不能捕捉健康个体之间的自然变化。最近提出了一种从综合数据的荟萃分析中估计参考范围的方法,该方法同时考虑了个体内和个体间的变异。在本指南中,我们介绍了 3 种估计参考范围的方法:1 种是频率论的,1 种是贝叶斯的,1 种是经验的。每种方法都可以应用于综合或个体参与者数据荟萃分析,当可用时后者是金标准。我们将这些方法应用于先前发表的个体参与者数据荟萃分析的数据,该分析于 2006 年至 2016 年期间在健康个体中通过瞬时弹性成像测量肝脏硬度。