Home Reference intervals in value-based laboratory medicine: a shift from single-point measurements to metabolic variation-based models
Article
Licensed
Unlicensed Requires Authentication

Reference intervals in value-based laboratory medicine: a shift from single-point measurements to metabolic variation-based models

  • Abdurrahman Coskun ORCID logo EMAIL logo and Mario Plebani ORCID logo
Published/Copyright: August 18, 2025
Become an author with De Gruyter Brill
Submit Manuscript Author Information
Clinical Chemistry and Laboratory Medicine (CCLM)
From the journal Clinical Chemistry and Laboratory Medicine (CCLM) Volume 63 Issue 11

Abstract

Laboratory data can be meaningful only when compared with reliable reference data; therefore, the estimation of reliable reference data is just as important as the accurate measurement of measurands in patient samples. Since analyte concentrations in the human body are influenced by both random variations (such as biological fluctuations) and systematic variations (such as physiological rhythms and age-related changes), the conventional model for estimating reference data – based solely on the statistical distribution of single-sample measurements from reference individuals – may not provide sufficiently reliable information for interpreting patient results. Therefore, a paradigm shift from relying solely on single-sample measurement distributions to incorporating metabolic changes observed in the human body when estimating reference intervals may enhance the clinical value of laboratory data for an effective clinical decision making and patient care. This opinion paper aims to summarize how to facilitate this transition and to identify the most suitable model for estimating reference intervals that reflect underlying metabolic dynamics.

Keywords: biological variation; personalized reference intervals; population-based reference intervals; reference intervals; value-based laboratory medicine
Corresponding author: Abdurrahman Coskun, Department of Medical Biochemistry, School of Medicine, Acibadem Mehmet Ali Aydinlar University, Istanbul, Türkiye; E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: The grammar and style of the English in the manuscript were improved with the assistance of ChatGPT (Open AI).

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: None declared.

References

1. Horowitz, GL, Altaie, S, Boyd, JC, Ceriotti, F, Garg, U, Horn, P, et al.. EP28-A3c: defining, establishing, and verifying reference intervals in the clinical laboratory; approved guideline – third edition. Clin Lab Stand Institute 2010;28:12.Search in Google Scholar

2. Coskun, A, Lippi, G. The impact of physiological variations on personalized reference intervals and decision limits: an in-depth analysis. Clin Chem Lab Med 2024;62:2140–7. https://doi.org/10.1515/cclm-2024-0009.Search in Google Scholar PubMed

3. Coskun, A. Diagnosis based on population data versus personalized data: the evolving paradigm in laboratory medicine. Diagn 2024;14:2135. https://doi.org/10.3390/diagnostics14192135.Search in Google Scholar PubMed PubMed Central

4. Coskun, A. Are your laboratory data reproducible? The critical role of imprecision from replicate measurements to clinical decision-making. Ann Lab Med 2025;45:259–71. https://doi.org/10.3343/alm.2024.0569.Search in Google Scholar PubMed PubMed Central

5. Coskun, A, Sandberg, S, Unsal, I, Yavuz, FG, Cavusoglu, C, Serteser, M, et al.. Personalized reference intervals – statistical approaches and considerations. Clin Chem Lab Med 2021;60:629–35. https://doi.org/10.1515/cclm-2021-1066.Search in Google Scholar PubMed

6. Coskun, A, Sandberg, S, Unsal, I, Serteser, M, Aarsand, AK. Personalized reference intervals: from theory to practice. Crit Rev Clin Lab Sci 2022;59:501–16. https://doi.org/10.1080/10408363.2022.2070905.Search in Google Scholar PubMed

7. Coskun, A, Zarepour, A, Zarrabi, A. Physiological rhythms and biological variation of biomolecules: the road to personalized laboratory medicine. Int J Mol Sci 2023;24:6275. https://doi.org/10.3390/ijms24076275.Search in Google Scholar PubMed PubMed Central

8. Siest, G, Henny, J, Gräsbeck, R, Wilding, P, Petitclerc, C, Queraltó, JM, et al.. The theory of reference values: an unfinished symphony. Clin Chem Lab Med 2013;51:47–64. https://doi.org/10.1515/cclm-2012-0682.Search in Google Scholar PubMed

9. Meex, SJR, Aakre, KM. Personalized ranges for blood-test results enable precision diagnostics. Nature 2024;637:279–80. https://doi.org/10.1038/d41586-024-03854-9. 8045 2024;637.Search in Google Scholar PubMed

10. Foy, BH, Petherbridge, R, Roth, MT, Zhang, C, De Souza, DC, Mow, C, et al.. Haematological setpoints are a stable and patient-specific deep phenotype. Nature 2025;637:430–8. https://doi.org/10.1038/s41586-024-08264-5.Search in Google Scholar PubMed PubMed Central

11. Patharkar, A, Cai, F, Al-Hindawi, F, Wu, T. Predictive modeling of biomedical temporal data in healthcare applications: review and future directions. Front Physiol 2024;15:1386760. https://doi.org/10.3389/fphys.2024.1386760.Search in Google Scholar PubMed PubMed Central

12. Zeger, SL, Irizarry, R, Peng, RD. On time series analysis of public health and biomedical data. Annu Rev Publ Health 2006;27:57–79. https://doi.org/10.1146/annurev.publhealth.26.021304.144517.Search in Google Scholar PubMed

13. Pinsky, MA. Introduction to fourier analysis and wavelets. Providence, Rhode Island: American Mathematical Society; 2008:376 p.Search in Google Scholar

14. Coskun, A, Savas, IN, Can, O, Lippi, G. From population-based to personalized laboratory medicine: continuous monitoring of individual laboratory data with wearable biosensors. Crit Rev Clin Lab Sci 2025;62:198–227. https://doi.org/10.1080/10408363.2025.2453152.Search in Google Scholar PubMed

15. Lehman, LWH, Adams, RP, Mayaud, L, Moody, GB, Malhotra, A, Mark, RG, et al.. A physiological time series dynamics-based approach to patient monitoring and outcome prediction. IEEE J Biomed Health Inform 2014;19:1068. https://doi.org/10.1109/jbhi.2014.2330827.Search in Google Scholar

16. Sebastiani, P, Monti, S, Lustgarten, MS, Song, Z, Ellis, D, Tian, Q, et al.. Metabolite signatures of chronological age, aging, survival, and longevity. Cell Rep 2024;43:114913. https://doi.org/10.1016/j.celrep.2024.114913.Search in Google Scholar PubMed PubMed Central

17. Oh, HSH, Rutledge, J, Nachun, D, Pálovics, R, Abiose, O, Moran-Losada, P, et al.. Organ aging signatures in the plasma proteome track health and disease. Nature 2023;624:164–72. https://doi.org/10.1038/s41586-023-06802-1.Search in Google Scholar PubMed PubMed Central

18. Meeker, WQ, Hahn, GJ, Escobar, LA. Statistical intervals: a guide for practitioners and researchers. New Jersey: Wiley; 2017:648 p.10.1002/9781118594841Search in Google Scholar

19. Aarsand, AK, Webster, C, Fernandez-Calle, P, Jonker, N, Diaz-Garzon, J, Coskun, A, et al. The EFLM biological variation database. https://biologicalvariation.eu. (accesed July 2025)Search in Google Scholar

20. Plebani, M. The detection and prevention of errors in laboratory medicine. Ann Clin Biochem 2010;47:101–10. https://doi.org/10.1258/acb.2009.009222.Search in Google Scholar PubMed

21. Plebani, M. Errors in clinical laboratories or errors in laboratory medicine? Clin Chem Lab Med 2006;44:750–9. https://doi.org/10.1515/cclm.2006.123.Search in Google Scholar PubMed

22. Plebani, M. Errors in laboratory medicine and patient safety: the road ahead. Clin Chem Lab Med 2007;45:700–7. https://doi.org/10.1515/cclm.2007.170.Search in Google Scholar

23. Coşkun, A, Sandberg, S, Unsal, I, Topcu, DI, Aarsand, AK. Reference intervals revisited: a novel model for population-based reference intervals, using a small sample size and biological variation data. Clin Chem 2024;70:1279–90. https://doi.org/10.1093/clinchem/hvae109.Search in Google Scholar PubMed

24. Aarsand, AK, Røraas, T, Fernandez-Calle, P, Ricos, C, Díaz-Garzón, J, Jonker, N. European Federation of Clinical Chemistry and Laboratory Medicine Working Group on Biological Variation and Task and Finish Group for the Biological Variation Database. The biological variation data critical appraisal checklist: a standard for evaluating studies on biological variation. Clin Chem 2018;64:501–14. https://doi.org/10.1373/clinchem.2017.281808.Search in Google Scholar PubMed

25. Doyle, K, Bunch, DR. Reference intervals: past, present, and future. Crit Rev Clin Lab Sci 2023;60:466–82. https://doi.org/10.1080/10408363.2023.2196746.Search in Google Scholar PubMed

26. Plebani, M, Coskun, A. Promoting value-based laboratory medicine: moving towards an innovative model of clinical laboratory. Clin Chim Acta 2025;572:120269. https://doi.org/10.1016/j.cca.2025.120269.Search in Google Scholar PubMed

Received: 2025-06-19
Accepted: 2025-07-21
Published Online: 2025-08-18
Published in Print: 2025-10-27

© 2025 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Advancing diagnostic stewardship through claims-based utilization analysis: toward a system-wide vision of diagnostic excellence
  4. Review
  5. Biomarkers in body fluids and their detection techniques for human intestinal permeability assessment
  6. Mini Review
  7. Challenges of using natriuretic peptides to screen for the risk of developing heart failure in patients with diabetes: a report from the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Committee on Clinical Applications of Cardiac Bio-Markers (C-CB)
  8. Opinion Papers
  9. Reference intervals in value-based laboratory medicine: a shift from single-point measurements to metabolic variation-based models
  10. Overview of laboratory diagnostics for immediate management of patients presenting to the emergency department with acute bleeding
  11. What Matters Most: an Age-Friendly approach to pathology and laboratory medicine
  12. No fault or negligence after an adverse analytical finding due to a contaminated supplement: mission impossible. Two examples involving trimetazidine
  13. General Clinical Chemistry and Laboratory Medicine
  14. Utilization analysis of laboratory tests using health insurance claims data: advancing nationwide diagnostic stewardship monitoring systems
  15. Evaluating large language models as clinical laboratory test recommenders in primary and emergency care: a crucial step in clinical decision making
  16. A novel corrective model based on red blood cells indices and haemolysis index enables accurate unhaemolysed potassium determination in haemolysed samples – Hemokalc project
  17. Validation of (self-collected) capillary blood using a topper collection system as alternative for venous sampling for 15 common clinical chemistry analytes
  18. Acoustophoresis-based blood sampling and plasma separation for potentially minimizing sampling-related blood loss
  19. Clinical validation of a liquid chromatography single quadrupole mass spectrometry (LC-MS) method using Waters Kairos™ Amino Acid Kit reagents
  20. Robustness of steroidomics-based machine learning for diagnosis of primary aldosteronism: a laboratory medicine perspective
  21. Investigation of the possible cause of over-estimation of human aldosterone in plasma, using a unique, non-synthetic human aldosterone-free matrix
  22. Performance of afternoon (16:00 h) serum cortisol for the diagnosis of Cushing’s syndrome
  23. MAGLUMI® Tacrolimus (CLIA) assay: analytical performances and comparison with LC-MS/MS and ARCHITECT Tacrolimus (CMIA) assay
  24. Assessment of 2023 ACR/EULAR antiphospholipid syndrome classification criteria in a Spanish cohort
  25. Comprehensive evaluation of antiphospholipid antibody testing methodologies in APS diagnosis: performance comparisons across assay systems and clinical subtypes
  26. Candidate Reference Measurement Procedures and Materials
  27. Exploring commutable materials for serum folate measurement: challenges in cross-method harmonization
  28. Reference Values and Biological Variations
  29. Reference ranges for ionized calcium in plasma in Danish children aged 0 days to 3 years using laboratory registry data
  30. A step forward in pediatric hemophagocytic lymphohistiocytosis and autoimmune disease: pediatric reference interval for serum soluble IL-2 receptor and soluble CD163
  31. Cancer Diagnostics
  32. Cellular expression of PD-1, PD-L1 and CTLA-4 in patients with JAK2V617F mutated myeloproliferative disorders
  33. Diabetes
  34. Serum N-glycans as independent predictors of the incidence of type 2 diabetes: a prospective investigation in the AEGIS cohort
  35. Infectious Diseases
  36. An assessment of molecular diagnosis of tuberculosis and multi-drug resistant tuberculosis testing and quality assessment: findings of an international survey
  37. Letters to the Editor
  38. Targeting low-value laboratory care
  39. Is time a significant factor in the release of potassium from lithium heparin plasma and serum?
  40. External quality assessment in resource-constrained laboratories: a survey of practices and perceptions in Nepal
  41. Is successfulness of platelet clump disaggregation by vortexing influenced by platelet measurement methods?
  42. Oligoclonal banding analysis: assessing plasma use and time interval requirements for paired CSF and blood
https://doi.org/10.1515/cclm-2025-0763
Keywords for this article
biological variation; personalized reference intervals; population-based reference intervals; reference intervals; value-based laboratory medicine

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Advancing diagnostic stewardship through claims-based utilization analysis: toward a system-wide vision of diagnostic excellence
  4. Review
  5. Biomarkers in body fluids and their detection techniques for human intestinal permeability assessment
  6. Mini Review
  7. Challenges of using natriuretic peptides to screen for the risk of developing heart failure in patients with diabetes: a report from the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Committee on Clinical Applications of Cardiac Bio-Markers (C-CB)
  8. Opinion Papers
  9. Reference intervals in value-based laboratory medicine: a shift from single-point measurements to metabolic variation-based models
  10. Overview of laboratory diagnostics for immediate management of patients presenting to the emergency department with acute bleeding
  11. What Matters Most: an Age-Friendly approach to pathology and laboratory medicine
  12. No fault or negligence after an adverse analytical finding due to a contaminated supplement: mission impossible. Two examples involving trimetazidine
  13. General Clinical Chemistry and Laboratory Medicine
  14. Utilization analysis of laboratory tests using health insurance claims data: advancing nationwide diagnostic stewardship monitoring systems
  15. Evaluating large language models as clinical laboratory test recommenders in primary and emergency care: a crucial step in clinical decision making
  16. A novel corrective model based on red blood cells indices and haemolysis index enables accurate unhaemolysed potassium determination in haemolysed samples – Hemokalc project
  17. Validation of (self-collected) capillary blood using a topper collection system as alternative for venous sampling for 15 common clinical chemistry analytes
  18. Acoustophoresis-based blood sampling and plasma separation for potentially minimizing sampling-related blood loss
  19. Clinical validation of a liquid chromatography single quadrupole mass spectrometry (LC-MS) method using Waters Kairos™ Amino Acid Kit reagents
  20. Robustness of steroidomics-based machine learning for diagnosis of primary aldosteronism: a laboratory medicine perspective
  21. Investigation of the possible cause of over-estimation of human aldosterone in plasma, using a unique, non-synthetic human aldosterone-free matrix
  22. Performance of afternoon (16:00 h) serum cortisol for the diagnosis of Cushing’s syndrome
  23. MAGLUMI® Tacrolimus (CLIA) assay: analytical performances and comparison with LC-MS/MS and ARCHITECT Tacrolimus (CMIA) assay
  24. Assessment of 2023 ACR/EULAR antiphospholipid syndrome classification criteria in a Spanish cohort
  25. Comprehensive evaluation of antiphospholipid antibody testing methodologies in APS diagnosis: performance comparisons across assay systems and clinical subtypes
  26. Candidate Reference Measurement Procedures and Materials
  27. Exploring commutable materials for serum folate measurement: challenges in cross-method harmonization
  28. Reference Values and Biological Variations
  29. Reference ranges for ionized calcium in plasma in Danish children aged 0 days to 3 years using laboratory registry data
  30. A step forward in pediatric hemophagocytic lymphohistiocytosis and autoimmune disease: pediatric reference interval for serum soluble IL-2 receptor and soluble CD163
  31. Cancer Diagnostics
  32. Cellular expression of PD-1, PD-L1 and CTLA-4 in patients with JAK2V617F mutated myeloproliferative disorders
  33. Diabetes
  34. Serum N-glycans as independent predictors of the incidence of type 2 diabetes: a prospective investigation in the AEGIS cohort
  35. Infectious Diseases
  36. An assessment of molecular diagnosis of tuberculosis and multi-drug resistant tuberculosis testing and quality assessment: findings of an international survey
  37. Letters to the Editor
  38. Targeting low-value laboratory care
  39. Is time a significant factor in the release of potassium from lithium heparin plasma and serum?
  40. External quality assessment in resource-constrained laboratories: a survey of practices and perceptions in Nepal
  41. Is successfulness of platelet clump disaggregation by vortexing influenced by platelet measurement methods?
  42. Oligoclonal banding analysis: assessing plasma use and time interval requirements for paired CSF and blood
Sign up now to receive a 20% welcome discount
Institutional Access
How does access work?
Have an idea on how to improve our website?
Please write us.
© 2025 De Gruyter Brill
Downloaded on 10.10.2025 from https://www.degruyterbrill.com/document/doi/10.1515/cclm-2025-0763/html?recommended=sidebar
Scroll to top button