Similarity analysis of blood count reference intervals reveals no ethnic or geographic structure and supports personalised values

Abstract Blood reference intervals (RIs) underpin diagnostic interpretation and therapeutic monitoring worldwide. However, many widely used RI systems originate from limited historical cohorts and have been propagated across health systems without harmonised derivation protocols, shared metadata, or cross-population validation. Here, we examine published complete blood count (CBC) reference intervals, one of the most commonly used laboratory panels worldwide. We compiled CBC RI data from 28 countries and analysed their similarity using variability mapping, hierarchical clustering, information-theoretic distances, cohesion benchmarking, and nonlinear manifold visualisation. Body mass index (BMI) served as a methodological positive benchmark and showed clear continent-level clustering. In contrast, CBC reference intervals showed no reproducible geography-linked clustering across analytical methods, with uniformly high cohesion scores, which would have been expected if RIs were biologically or genetically relevant or specific to their populations. Weak signals in red-cell indices were unstable across sexes and distance metrics. This absence of structure should not be interpreted as evidence that current CBC reference intervals represent universal biological standards. Rather, it is more consistent with the fragmented and historically inherited nature of the global RI landscape. These findings indicate that published CBC reference intervals do not encode coherent global structure and support a transition toward recalibrated and personalised reference frameworks based on longitudinal individual baselines and harmonised derivation standards.

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Publication Details

Journal
npj Digital Public Health
Published
2026-09-07
DOI
https://doi.org/10.1038/s44482-026-00035-5
Primary Topic
Clinical Laboratory Practices and Quality Control
Type
article
Field-Weighted Citation Impact
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article

Similarity analysis of blood count reference intervals reveals no ethnic or geographic structure and supports personalised values

Héctor Zenil, Kanke Wu, Abicumaran Uthamacumaran
npj Digital Public Health
Clinical Laboratory Practices and Quality Control
article

Similarity analysis of blood count reference intervals reveals no ethnic or geographic structure and supports personalised values

Héctor Zenil, Kanke Wu, Abicumaran Uthamacumaran
article en

Abstract

Abstract Blood reference intervals (RIs) underpin diagnostic interpretation and therapeutic monitoring worldwide. However, many widely used RI systems originate from limited historical cohorts and have been propagated across health systems without harmonised derivation protocols, shared metadata, or cross-population validation. Here, we examine published complete blood count (CBC) reference intervals, one of the most commonly used laboratory panels worldwide. We compiled CBC RI data from 28 countries and analysed their similarity using variability mapping, hierarchical clustering, information-theoretic distances, cohesion benchmarking, and nonlinear manifold visualisation. Body mass index (BMI) served as a methodological positive benchmark and showed clear continent-level clustering. In contrast, CBC reference intervals showed no reproducible geography-linked clustering across analytical methods, with uniformly high cohesion scores, which would have been expected if RIs were biologically or genetically relevant or specific to their populations. Weak signals in red-cell indices were unstable across sexes and distance metrics. This absence of structure should not be interpreted as evidence that current CBC reference intervals represent universal biological standards. Rather, it is more consistent with the fragmented and historically inherited nature of the global RI landscape. These findings indicate that published CBC reference intervals do not encode coherent global structure and support a transition toward recalibrated and personalised reference frameworks based on longitudinal individual baselines and harmonised derivation standards.

npj Digital Public HealthVol. 1(1)
King's College London (GB), Kings Health Partners (GB), Centre for Sustainable Healthcare (GB)
Openalex Percentile: Top 11%
Clinical Laboratory Practices and Quality Control
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