A0222
Title: A guide to estimating the reference range from a meta-analysis using aggregate or individual participant data
Authors: Lianne Siegel - University of Minnesota School of Public Health (United States)
Hassan Murad - Mayo Clinic (United States)
Richard Riley - Keele University (United Kingdom)
Fateh Bazerbachi - St Cloud Hospital (United States)
Zhen Wang - Mayo Clinic (United States)
Haitao Chu - University of Minnesota School of Public Health (United States) [presenting]
Abstract: Clinicians frequently must decide whether a patients 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 or the prediction interval for a new study mean in a meta-analysis, which does not capture natural variation across healthy individuals. Methods for estimating the reference range from a meta-analysis of aggregate data that incorporate both within and between-study variations were recently proposed. We present three approaches for estimating the reference range: a frequentist, a Bayesian, and an empirical method. Each method can be applied to either aggregate or individual participant data (IPD) meta-analysis, with the latter being the gold standard when available. We illustrate these approaches using a clinical scenario about the normal range of a liver stiffness test.
