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The STARD Statement for Reporting Studies of Diagnostic Accuracy: Explanation and Elaboration
Abstract
The quality of reporting of studies of diagnostic accuracy is less than optimal. Complete and accurate reporting is necessary to enable readers to assess the potential for bias in the study and to evaluate the generalizability of the results. A group of scientists and editors has developed the STARD (Standards for Reporting of Diagnostic Accuracy) statement to improve the reporting the quality of reporting of studies of diagnostic accuracy. The statement consists of a checklist of 25 items and flow diagram that authors can use to ensure that all relevant information is present. This explanatory document aims to facilitate the use, understanding, and dissemination of the checklist. The document contains a clarification of the meaning, rationale, and optimal use of each item on the checklist, as well as a short summary of the available evidence on bias and applicability. The STARD statement, checklist, flowchart, and this explanation and elaboration document should be useful resources to improve reporting of diagnostic accuracy studies. Complete and informative reporting can only lead to better decisions in health care.
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“By outlining a list of 30 minimum essential items that should be reported for every diagnostic test accuracy study, STARD can improve the quality of study reporting, help stakeholders judge the risk of bias and applicability of the findings and enhance research reproducibility.”
From The STARD-AI reporting guideline for diagnostic accuracy studies using artificial intelligence (2025) · cites this paper as [13]
In the citing paper
“In response to this, the STARD statement was developed in 2003, and was subsequently updated in 2015 (STARD 2015), to standardize the reporting of diagnostic accuracy research 13,14 .”
From The STARD-AI reporting guideline for diagnostic accuracy studies using artificial intelligence (2025) · cites this paper as [13]
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Metadata
- Authors
- Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., Moher, D., Rennie, D., de Vet, H. C. W., & Lijmer, J. G.
- Affiliations
- Amsterdam UMC Location University of Amsterdam (NL)
- University of Virginia (US)
- Brown University (US)
- The University of Queensland (AU)
- The University of Sydney (AU)
- From Academic Medical Center and VU University Medical Center, Amsterdam, the Netherlands; Clinical Chemistry, Charlottesville, Virginia; Brown University, Providence, Rhode Island; University of Queensland Medical School, Herston, Australia; University of Sydney, Sydney, Australia; Thomas C. Chalmers Center for Systematic Reviews, Ottawa, Ontario, Canada; and Journal of the American Medical Association, Chicago, Illinois.
- American Medical Association (US)
- Vrije Universiteit Amsterdam (NL)
- Corresponding author
- Bossuyt, Patrick M.
- ORCID
- Venue
- Annals of Internal Medicine
- Publisher
- American College of Physicians
- Published
- 2003-01-07
- Volume
- 138
- Issue
- 1
- Pages
- W1-12
- ISSN
- 0009-9147 (ISSN-L)
- 0003-4819
- 1539-3704
- OpenAlex
- W1498589284
- Cited by
- 1,124
- References
- 92
- Citations by year
- 2026: 5 · 2025: 8 · 2024: 13 · 2023: 12 · 2022: 14 · 2021: 20 · 2020: 28 · 2019: 37 · 2018: 45 · 2017: 47 · 2016: 47 · 2015: 97 · 2014: 86 · 2013: 74 · 2012: 89
- FWCI
- 69.44
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Clinical Chemistry (publishedVersion)
- Annals of Internal Medicine (publishedVersion)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Pure Amsterdam UMC (submittedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Clinical practice guidelines implementation
- Keywords
- diagnostic accuracy studies, reporting quality, reporting checklist, flowcharts, generalizability, applicability
- MeSH terms
- Algorithms, Clinical Trials as Topic, Publishing, Reference Standards, Research Design, Sensitivity and Specificity, Statistics as Topic, Reproducibility of Results, Bias, Diagnostic Techniques and Procedures
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