Personalized Reference Intervals in Laboratory Medicine: A New Model Based on Within-Subject Biological Variation.


Journal

Clinical chemistry
ISSN: 1530-8561
Titre abrégé: Clin Chem
Pays: England
ID NLM: 9421549

Informations de publication

Date de publication:
30 01 2021
Historique:
received: 16 05 2020
accepted: 10 09 2020
pubmed: 15 11 2020
medline: 23 9 2021
entrez: 14 11 2020
Statut: ppublish

Résumé

The concept of personalized medicine has received widespread attention in the last decade. However, personalized medicine depends on correct diagnosis and monitoring of patients, for which personalized reference intervals for laboratory tests may be beneficial. In this study, we propose a simple model to generate personalized reference intervals based on historical, previously analyzed results, and data on analytical and within-subject biological variation. A model using estimates of analytical and within-subject biological variation and previous test results was developed. We modeled the effect of adding an increasing number of measurement results on the estimation of the personal reference interval. We then used laboratory test results from 784 adult patients (>18 years) considered to be in a steady-state condition to calculate personalized reference intervals for 27 commonly requested clinical chemistry and hematology measurands. Increasing the number of measurements had little impact on the total variation around the true homeostatic set point and using ≥3 previous measurement results delivered robust personalized reference intervals. The personalized reference intervals of the study participants were different from one another and, as expected, located within the common reference interval. However, in general they made up only a small proportion of the population-based reference interval. Our study shows that, if using results from patients in steady state, only a few previous test results and reliable estimates of within-subject biological variation are required to calculate personalized reference intervals. This may be highly valuable for diagnosing patients as well as for follow-up and treatment.

Sections du résumé

BACKGROUND
The concept of personalized medicine has received widespread attention in the last decade. However, personalized medicine depends on correct diagnosis and monitoring of patients, for which personalized reference intervals for laboratory tests may be beneficial. In this study, we propose a simple model to generate personalized reference intervals based on historical, previously analyzed results, and data on analytical and within-subject biological variation.
METHODS
A model using estimates of analytical and within-subject biological variation and previous test results was developed. We modeled the effect of adding an increasing number of measurement results on the estimation of the personal reference interval. We then used laboratory test results from 784 adult patients (>18 years) considered to be in a steady-state condition to calculate personalized reference intervals for 27 commonly requested clinical chemistry and hematology measurands.
RESULTS
Increasing the number of measurements had little impact on the total variation around the true homeostatic set point and using ≥3 previous measurement results delivered robust personalized reference intervals. The personalized reference intervals of the study participants were different from one another and, as expected, located within the common reference interval. However, in general they made up only a small proportion of the population-based reference interval.
CONCLUSIONS
Our study shows that, if using results from patients in steady state, only a few previous test results and reliable estimates of within-subject biological variation are required to calculate personalized reference intervals. This may be highly valuable for diagnosing patients as well as for follow-up and treatment.

Identifiants

pubmed: 33188412
pii: 5981754
doi: 10.1093/clinchem/hvaa233
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

374-384

Informations de copyright

© American Association for Clinical Chemistry 2020. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Auteurs

Abdurrahman Coşkun (A)

Acibadem Labmed Clinical Laboratories.
Department of Medical Biochemistry, Acibadem Mehmet Ali Aydinlar University, School of Medicine, Istanbul, Turkey.

Sverre Sandberg (S)

Norwegian Organization for Quality Improvement of Laboratory Examinations (Noklus), Haraldsplass Deaconess Hospital, Bergen, Norway.
Department of Medical Biochemistry and Pharmacology, Norwegian Porphyria Centre, Haukeland University Hospital, Bergen, Norway.
Department of Global Health and Primary Care, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway.

Ibrahim Unsal (I)

Acibadem Labmed Clinical Laboratories.

Coskun Cavusoglu (C)

Acibadem Labmed Clinical Laboratories.

Mustafa Serteser (M)

Acibadem Labmed Clinical Laboratories.
Department of Medical Biochemistry, Acibadem Mehmet Ali Aydinlar University, School of Medicine, Istanbul, Turkey.

Meltem Kilercik (M)

Acibadem Labmed Clinical Laboratories.
Department of Medical Biochemistry, Acibadem Mehmet Ali Aydinlar University, School of Medicine, Istanbul, Turkey.

Aasne K Aarsand (AK)

Department of Medical Biochemistry and Pharmacology, Norwegian Porphyria Centre, Haukeland University Hospital, Bergen, Norway.
Department of Global Health and Primary Care, Faculty of Medicine and Dentistry, University of Bergen, Bergen, Norway.

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Classifications MeSH