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Likelihood ratios of quantitative diagnostic test results.

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Imperfect reference standards cause biased likelihood ratios.

Arne Åsberg1, Ann Elisabeth Åsberg1,2

  • 1Department of Clinical Chemistry, St. Olav Hospital, Trondheim University Hospital, Trondheim, Norway.

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|July 12, 2025
PubMed
Summary
This summary is machine-generated.

Imperfect reference standards can bias diagnostic biomarker accuracy. This study shows likelihood ratios (LRs) for biomarkers like S-transferrin saturation may be significantly misleading in diagnosing conditions such as iron deficiency.

Keywords:
Diagnostic accuracyimperfect reference standardiron deficiencylikelihood ratioreceiver operating characteristic (ROC) curvetransferrin saturation

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Area of Science:

  • Biomarker discovery and validation
  • Diagnostic test accuracy
  • Medical statistics

Background:

  • Quantitative biomarkers are crucial for disease diagnosis.
  • Diagnostic accuracy relies on reliable reference standards.
  • Imperfect reference standards can introduce bias in biomarker evaluation.

Purpose of the Study:

  • To investigate the impact of imperfect reference standards on diagnostic biomarker accuracy.
  • To quantify the bias in likelihood ratios (LRs) under various disease prevalence and biomarker-reference standard correlation scenarios.
  • To assess the clinical significance of this bias using iron deficiency diagnosis as an example.

Main Methods:

  • Utilized simulated datasets to model biomarker concentrations and reference standard classifications.
  • Varied disease prevalence and the correlation between the biomarker and the imperfect reference standard.
  • Analyzed the resulting bias in estimated receiver operating characteristic (ROC) curves and likelihood ratios (LRs).

Main Results:

  • Imperfect reference standards demonstrably bias the estimation of likelihood ratios (LRs).
  • The degree of bias is influenced by disease prevalence and the correlation between the biomarker and the reference standard.
  • Estimated LRs for S-transferrin saturation in iron deficiency diagnosis were shown to be potentially biased in a clinically significant manner.

Conclusions:

  • The use of imperfect reference standards can lead to misleading conclusions about a biomarker's diagnostic utility.
  • Careful consideration of reference standard quality is essential when evaluating quantitative biomarkers.
  • Findings highlight the need for robust validation methods to ensure reliable diagnostic biomarker assessment.