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Measuring Agreement in Diagnostics: A Practical Guide for Researchers.

Sophie Vanbelle1, Christina Hernandez Engelhart2,3, Ellen Blix3

  • 1Methodology and Statistics, CAPHRI, Maastricht University, Maastricht, Limburg, the Netherlands.

Statistics in Medicine
|October 17, 2025
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Summary
This summary is machine-generated.

This study clarifies how to compute and interpret agreement measures for binary clinical test results, crucial for patient care. It addresses methodological issues in reliability and agreement studies, enhancing diagnostic accuracy research.

Keywords:
clinical testconcordanceerrorinterobserverintraobserverobserver variationreliabilityrepeatabilityreproducibility of results

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Area of Science:

  • Biostatistics
  • Clinical Epidemiology
  • Medical Informatics

Background:

  • Clinical assessments require accurate interpretation for patient care.
  • Existing reliability and agreement studies in intrapartum fetal heart rate monitoring have methodological limitations.
  • Confusion exists between agreement and reliability, calculation methods for multiple raters, and reporting of confidence intervals.

Purpose of the Study:

  • To clarify computation and interpretation of agreement measures for binary outcomes.
  • To provide guidance on statistical inference and sample size calculations for agreement studies.
  • To enhance the methodological quality of diagnostic test agreement studies.

Main Methods:

  • Demonstration using a motivating example of five obstetricians assessing 20 CTGs (cardiotocography).
  • Explanation of agreement definitions, computation, and interpretation in various scenarios.
  • Discussion of the relationship between agreement, reliability, intra-observer, and inter-observer studies.

Main Results:

  • Emphasis on proportion of agreement, proportion of specific agreement, and kappa coefficients.
  • A developed shiny application to assist researchers in agreement studies.
  • The work complements existing reporting guidelines like GRRAS, QAREL, and STARD.

Conclusions:

  • Improved understanding and application of agreement measures in clinical research.
  • Enhanced methodological rigor in studies evaluating diagnostic test agreement.
  • Facilitation of more reliable diagnostic assessments and better patient outcomes.