A Parametric Empirical Bayes Approach to Personalized Reference Intervals and Reference Change Values.

ABSTRACT:

Background

Population-wide reference intervals (RIpop) are commonly used in laboratory medicine but may not reflect an individual's tightly regulated homeostatic interval. Personalized reference intervals (RIper) could enhance diagnostic precision by accounting for individual variability. A parametric empirical Bayes (PEB) framework stabilizes individual estimates using population parameters, enabling reliable RIper even from a limited number of individual results.

Methods

We applied the PEB framework to estimate RIper for 9 biomarkers: albumin, creatinine, phosphate, cortisone, cortisol, testosterone, androstenedione, 17-hydroxyprogesterone, and 11-deoxycortisol. The PEB parameters tested were derived from both routine Laboratory Information System (LIS) data and a local bi

SUBMITTER: Roys EA 

PROVIDER: S-EPMC12582661 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature