A Guide to Estimating the Reference Range From a Meta-Analysis Using Aggregate or Individual Participant Data

Lianne Siegel, M. Hassan Murad, Richard D. Riley, Fateh Bazerbachi, Zhen Wang, Haitao Chu

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)948-956
Number of pages9
JournalAmerican journal of epidemiology
Volume191
Issue number5
DOIs
StatePublished - May 1 2022

Keywords

  • meta-analysis
  • normative data
  • prediction interval
  • random effects
  • reference range

ASJC Scopus subject areas

  • Epidemiology

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