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Annual biological variation and personalized reference intervals of clinical chemistry and hematology analytes

Shuo Wang1, Min Zhao1, Zihan Su1

  • 1Department of Laboratory Medicine, The First Hospital of China Medical University, National Clinical Research Center for Laboratory Medicine, Shenyang, Liaoning, P.R. China.

Clinical Chemistry and Laboratory Medicine
|November 13, 2021
PubMed

Insights

Annual biological variation (BV) data offers more accurate lab result evaluation for health checkups. Personalized reference intervals (RIper) derived from long-term BV are valuable for individualized health assessments.

Area of Science:

  • Clinical Chemistry
  • Hematology
  • Biostatistics

Background:

  • Accurate laboratory criteria for evaluating health status during annual checkups are limited.
  • Annual biological variation (BV) and derived parameters are crucial for precise interpretation of laboratory results in healthcare populations.

Purpose of the Study:

  • To determine annual biological variation (BV) and key parameters for common laboratory analytes.
  • To establish personalized reference intervals (RIper) for improved health assessment accuracy.

Main Methods:

  • Collected annual laboratory data from 43 healthy individuals over six years.
  • Calculated annual BV, reference change value (RCV), index of individuality (II), and RIper.
  • Compared annual data parameters with weekly data and population-based reference intervals (RIpop).

Main Results:

  • Established annual BV (CV I), RCV, II, and RIper for 24 clinical chemistry and hematology analytes.
  • Annual CV I estimates were higher than weekly for 11 analytes.
  • Limited utility of RIpop for ~50% of analytes due to low II (<0.6); RIper showed limited overlap with RIpop.

Conclusions:

  • Annual BV and related parameters provide more accurate laboratory result evaluation for annual healthcare individuals compared to weekly BV.
  • RIper, based on long-term BV data, is highly valuable for personalized diagnosis in annual health assessments.
Abstract

Keywords:
biological variationindex of individualitypersonalized reference intervalsreference change valuereference intervals

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