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Following the Dynamics of Structural Variants in Experimentally Evolved Populations
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Biological variation: recent development and future challenges.

Sverre Sandberg1,2,3, Anna Carobene4, Bill Bartlett5

  • 1Norwegian Organization for Quality Improvement of Laboratory Examinations (Noklus), Haraldsplass Deaconess Hospital, Bergen, Norway.

Clinical Chemistry and Laboratory Medicine
|December 20, 2022
PubMed
Summary
This summary is machine-generated.

Biological variation (BV) data are crucial for laboratory medicine, enabling applications like setting performance specifications and personalized reference intervals. Recent advancements focus on robust data acquisition and novel applications, enhancing diagnostic accuracy.

Keywords:
BIVACEuBIVASbiological variationpersonalized reference intervals (prRI)reference change value

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Area of Science:

  • Laboratory medicine
  • Clinical chemistry
  • Biostatistics

Background:

  • Biological variation (BV) data are essential for numerous laboratory medicine applications.
  • The utility of BV data hinges on their relevance, robustness, and fitness for purpose.
  • Data can be acquired through experimental studies or analysis of routine laboratory results.

Purpose of the Study:

  • To review major achievements in biological variation data over the past decade.
  • To discuss advancements in deriving and applying BV data.
  • To highlight new standards and databases for BV data.

Main Methods:

  • Review of recent literature and studies on biological variation.
  • Discussion of new models and approaches for deriving BV data.
  • Presentation of data from large-scale studies like the European Biological Variation Study (EuBIVAS).

Main Results:

  • Development of new models and approaches for BV data derivation.
  • Establishment of high-quality BV data through EuBIVAS.
  • Introduction of standards like the Biological Variation Data Critical Appraisal Checklist (BIVAC).
  • Creation of the EFLM Biological Variation Database.
  • Expansion of BV data applications, including personalized reference intervals and measurement uncertainty.

Conclusions:

  • Significant progress has been made in acquiring and utilizing biological variation data.
  • Standardized methods and databases are improving data quality and accessibility.
  • New applications are emerging, promising more personalized and accurate laboratory diagnostics.