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Within-subject biological variation in disease: collated data and clinical consequences
Carmen Ricós1, Natalia Iglesias, José-Vicente García-Lario
1Analytical Quality Commission of the Spanish Society of Clinical Biochemistry and Molecular Pathology (SEQC), Barcelona, Spain. cricos@vhebron.net
Annals of Clinical Biochemistry
|June 28, 2007
Summary
Biological variation (BV) data in disease helps assess patient results. While most biological variation coefficients (CV(I)) are similar in health and disease, disease-specific reference change values (RCV) may be needed for certain markers.
Area of Science:
- Clinical Chemistry
- Biostatistics
- Laboratory Medicine
Background:
- Biological variation (BV) data is crucial for interpreting serial laboratory test results.
- Pathology can alter baseline levels and variability of biomarkers in patients.
- Understanding BV in disease states is essential for accurate clinical interpretation.
Purpose of the Study:
- To compile and analyze published BV data for individuals with diseases.
- To compare within-subject coefficient of variation (CV(I)) in disease versus healthy states.
- To evaluate the clinical utility of disease-specific BV data for monitoring patients.
Main Methods:
- Systematic collation of published within-subject coefficient of variation (CV(I)) data.
- Inclusion of 66 quantities across 34 disease states.
- Comparison of CV(I) in diseased individuals with established values from healthy populations.
Main Results:
- For most quantities, CV(I) values were comparable between healthy individuals and those with disease.
- A subset of quantities, identified as potential disease-specific markers, showed different CV(I) in disease.
- The findings suggest that standard reference change values (RCV) may be applicable for many tests, but not all.
Conclusions:
- The majority of biological variation data in disease mirrors that of healthy states, supporting the general use of RCV derived from healthy populations.
- Disease-specific RCVs may be necessary for certain biomarkers where variation differs significantly between health and disease.
- Tailoring RCVs to specific disease states could enhance the clinical utility of monitoring patient results.
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