Reporting quality of diagnostic accuracy studies: a systematic review and meta-analysis of investigations on adherence to STARD
Open accessAbstract
BACKGROUND: Poor reporting of diagnostic accuracy studies impedes an objective appraisal of the clinical performance of diagnostic tests. The Standards for Reporting of Diagnostic Accuracy Studies (STARD) statement, first published in 2003, aims to improve the reporting quality of such studies. OBJECTIVE: To investigate to which extent published diagnostic accuracy studies adhere to the 25-item STARD checklist, whether the reporting quality has improved after STARD's launch and whether there are any factors associated with adherence. STUDY SELECTION: We performed a systematic review and searched MEDLINE, EMBASE and the Methodology Register of the Cochrane Library for studies that primarily aimed to examine the reporting quality of articles on diagnostic accuracy studies in humans by evaluating adherence to STARD. Study selection was performed in duplicate; data were extracted by one author and verified by the second author. FINDINGS: We included 16 studies, analysing 1496 articles in total. Three studies investigated adherence in a general sample of diagnostic accuracy studies; the others did so in a specific field of research. The overall mean number of items reported varied from 9.1 to 14.3 between 13 evaluations that evaluated all 25 STARD items. Six studies quantitatively compared post-STARD with pre-STARD articles. Combining these results in a random-effects meta-analysis revealed a modest but significant increase in adherence after STARD's introduction (mean difference 1.41 items (95% CI 0.65 to 2.18)). CONCLUSIONS: The reporting quality of diagnostic accuracy studies was consistently moderate, at least through halfway the 2000s. Our results suggest a small improvement in the years after the introduction of STARD. Adherence to STARD should be further promoted among researchers, editors and peer reviewers.
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Since publication of STARD, several evaluations have pointed to small but statistically significant improvements in reporting accuracy studies, with a mean gain of 1.4 items (95% CI 0.7 to 2.2).
“Since the publication of STARD, several evaluations have pointed to small but statistically significant improvements in reporting accuracy studies (mean gain 1.4 items (95% confidence interval 0.7 to 2.2)).5 10”
From STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies (2015) · cites this paper as [10]
Evidence suggests that adherence to STARD improves the reporting of key information in diagnostic test accuracy studies.
“Evidence suggests that adherence to STARD improves the reporting of key information in diagnostic test accuracy studies 17,18 .”
From The STARD-AI reporting guideline for diagnostic accuracy studies using artificial intelligence (2025) · cites this paper as [18]
Adherence to the STARD checklist leads to improved reporting of key study parameters.
“studies have shown that adherence to the STARD checklist leads to improved reporting of key study parameters.7 8”
From Developing a reporting guideline for artificial intelligence-centred diagnostic test accuracy studies: the STARD-AI protocol (2021) · cites this paper as [7]
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- Authors
- Korevaar, D. A., van Enst, W. A., Spijker, R., Bossuyt, P. M. M., & Hooft, L.
- Affiliations
- Amsterdam UMC Location University of Amsterdam (NL)
- Venue
- Evidence Based Medicine
- Publisher
- BMJ
- Published
- 2013-12-24
- Volume
- 19
- Issue
- 2
- Pages
- 47-54
- ISSN
- 1356-5524 (ISSN-L)
- 1473-6810
- OpenAlex
- W1963909263
- Cited by
- 119
- References
- 35
- Citations by year
- 2026: 7 · 2025: 5 · 2024: 5 · 2023: 11 · 2022: 7 · 2021: 12 · 2020: 3 · 2019: 12 · 2018: 7 · 2017: 12 · 2016: 15 · 2015: 14 · 2014: 9
- FWCI
- 2.62
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- BMJ Evidence-Based Medicine (publishedVersion)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- HighWire Press Open Archive (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
- reporting quality, diagnostic accuracy studies, reporting guidelines adherence, diagnostic performance, peer review
- MeSH terms
- Diagnostic Tests, Routine, Humans, Quality Control, Practice Guidelines as Topic, Guideline Adherence, Checklist
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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