ArticleStatistics in medicine2025
Measuring Agreement in Diagnostics: A Practical Guide for Researchers.
Article in Statistics in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Evaluation of the diagnostic capacities of saliva sampling from pediatric patients: Protocol for a randomized intra-individual study.MethodsX · 2026Article
- Agreement testing of AMSTAR-PF, a tool for quality appraisal of systematic reviews of prognostic factor studies.BMJ open · 2026Observational
- Development and internal validation of a LASSO-based clinical prediction model for nontuberculous mycobacterial pulmonary disease versus pulmonary tuberculosis.Frontiers in medicine · 2026Article
- Measuring Agreement in Diagnostics: A Practical Guide for Researchers.Statistics in medicine · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Healthcare professionals routinely perform clinical examinations and diagnostic assessments. How the findings of these assessments are interpreted can have significant implications for patient care and outcomes. A recent systematic review on reliability and agreement studies in intrapartum fetal heart rate monitoring highlighted three methodological issues: (1) confusion between the concepts of agreement and reliability, (2) lack of clarity on how agreement and reliability measures are calculated when more than two raters are involved, and (3) confidence intervals seldom reported. This paper aims to clarify how agreement measures can be computed and interpreted when the outcome is binary (e.g., normal/abnormal test result). Using a motivating example in which five experienced obstetricians assessed 20 CTGs, we demonstrate how agreement can be defined, computed, and interpreted in various scenarios. The paper further explains the relationship between agreement measures and the concept of reliability, the distinction between intra- and inter-observer studies, and approaches to make statistical inference and sample size calculations. Particular emphasis is placed on the proportion of agreement, the proportion of specific agreement and kappa coefficients. A shiny application has also been developed to support researchers in their agreement studies. This work completes existing tools such as the Guidelines for Reporting Reliability and Agreement Studies (GRRAS), the Quality Appraisal Tool for Studies of Diagnostic Reliability (QAREL) and STARD guidelines for reporting diagnostic accuracy studies. It is intended to help researchers improve the methodological quality of studies that evaluate the agreement of clinical tests.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.