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Related Experiment Videos

Are the common reference intervals truly common? Case studies on stratifying biochemical reference data by countries

A Lahti1

  • 1Department of Clinical Chemistry, Rikshospitalet University Hospital of Oslo, NO-0027 Oslo, Norway. Jari.lahti@rikshospitalet.no

Scandinavian Journal of Clinical and Laboratory Investigation
|June 30, 2004
PubMed
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A new method for partitioning biochemical reference data outperformed the Harris-Boyd method in a Nordic study. This suggests common reference intervals for enzymes like alkaline phosphatase (ALP), creatine kinase (CK), and gamma-glutamyl transpeptidase (GGT) are feasible across Nordic countries.

Area of Science:

  • Biochemistry
  • Clinical Chemistry
  • Biostatistics

Background:

  • The National Committee for Clinical Laboratory Standards (NCCLS) recommends the Harris-Boyd method for partitioning biochemical reference data.
  • Stratification of reference data is crucial for accurate clinical interpretation.
  • Previous methods may have limitations in handling complex data distributions.

Purpose of the Study:

  • To compare the efficacy of the Harris-Boyd method with a newly proposed method for partitioning biochemical reference data.
  • To evaluate these methods in the context of country-specific stratification of reference intervals for key enzymes.
  • To determine the feasibility of common reference intervals across Nordic countries.

Main Methods:

  • Comparative analysis of two partitioning methods: Harris-Boyd and a new direct estimation method.

Related Experiment Videos

  • Application of methods to reference data for alkaline phosphatase (ALP), creatine kinase (CK), and gamma-glutamyl transpeptidase (GGT) from the Nordic Reference Interval Project (NORIP).
  • Case studies involving stratification by country (Denmark, Finland, Norway, Sweden).

    • Main Results:

    • The new partitioning method showed deviations from the Harris-Boyd method for all three enzymes (ALP, CK, GGT) in pair-wise tests.
    • Neither method proved ideal for stratifying data into more than two subgroups.
    • Prevalence-adjusted analyses indicated no significant differences in partitioning criteria for the three enzymes across the four Nordic countries.

    Conclusions:

    • The Harris-Boyd method's performance was suboptimal compared to the new method for enzyme data partitioning.
    • Despite variations in CK and GGT between countries, common reference intervals are likely feasible for the studied enzymes in the Nordic region.
    • The findings support the potential application of common reference intervals for all tests within the NORIP project across Nordic countries.