The impact of physiological variations on personalized reference intervals and decision limits: an in-depth analysis

• Published in: Clinical chemistry and laboratory medicine Vol. 62; no. 11; pp. 2140 - 2147
• Main Authors: Coskun, Abdurrahman, Lippi, Giuseppe
• Format: Journal Article
• Language: English
• Published: Germany De Gruyter 28.10.2024; Walter De Gruyter & Company
• Subjects: biological variation; Biological Variation, Individual; Biomolecules; circadian rhythm; Circadian Rhythm - physiology; Circadian rhythms; Customization; Demographics; Demography; Ethnicity; Fault diagnosis; Fluctuations; Humans; Impact analysis; Intervals; personalized medicine; Physiological effects; Physiology; Precision Medicine; reference interval; Reference Values; Ultradian rhythms; Variation; biological variation; circadian rhythm; reference interval; personalized medicine
• ISSN: 1434-6621; 1437-4331; 1437-4331
• DOI: 10.1515/cclm-2024-0009

The interpretation of laboratory data is a comparative procedure. Physicians typically need reference values to compare patients’ laboratory data for clinical decisions. Therefore, establishing reliable reference data is essential for accurate diagnosis and patient monitoring. Human metabolism is a dynamic process. Various types of systematic and random fluctuations in the concentration/activity of biomolecules are observed in response to internal and external factors. In the human body, several biomolecules are under the influence of physiological rhythms and are therefore subject to ultradian, circadian and infradian fluctuations. In addition, most biomolecules are also characterized by random biological variations, which are referred to as biological fluctuations between subjects and within subjects/individuals. In routine practice, reference intervals based on population data are used, which by nature are not designed to capture physiological rhythms and random biological variations. To ensure safe and appropriate interpretation of patient laboratory data, reference intervals should be personalized and estimated using individual data in accordance with systematic and random variations. In this opinion paper, we outline (i) the main variations that contribute to the generation of personalized reference intervals (prRIs), (ii) the theoretical background of prRIs and (iii) propose new methods on how to harmonize prRIs with the systematic and random variations observed in metabolic activity, based on individuals’ demography.