ArticleBMJ evidence-based medicine2025
Post-publication peer review and the identification of methodological and reporting issues in COVID-19 trials: a qualitative study.
Article in BMJ evidence-based medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- A literature review and reflection on clinical trials: current challenges, future directions, and potential strategies to overcome practical barriers.AME clinical trials review · 2026Article
- Promoting informed health choices: the long and winding road.Journal of the Royal Society of Medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesWe aimed to determine to what extent systematic reviewers and post-preprint and post-publication peer review identified methodological and reporting issues in COVID-19 trials that could be easily resolved by the authors.
designQualitative study. DATA SOURCES: COVID-NMA living systematic review (covid-nma.com), PubPeer, medRxiv, Research Square, SSRN.
methodsWe considered randomised controlled trials (RCTs) in COVID-NMA that evaluated pharmacological treatments for COVID-19 and retrieved systematic reviewers' assessments of the risk of bias and outcome reporting bias. We also searched for commentary data on PubPeer and preprint servers up to 6 November 2023. We employed qualitative content analysis to develop themes and domains of methodological and reporting issues identified by commenters.
resultsWe identified 500 eligible RCTs. Systematic reviewers identified methodological and reporting issues in 446 (89%) RCTs. In 391 (78%) RCTs, the issues could be easily resolved by the trial authors; issues included incomplete reporting (49%), selection of the reported results (52%) and no access to the pre-specified plan (25%). Alternatively, 74 (15%) RCTs had received at least one comment on PubPeer or preprint servers, totalling 348 comments. In 46 (9%) RCTs, the issues identified by post-preprint and post-publication peer review comments could be easily resolved by the trial authors; the issues were related to incomplete reporting (6%), errors (5%), statistical analysis (3%), inconsistent reporting of methods and analyses (2%), spin (2%), selection of the reported results (1%) and no access to the raw data/pre-specified plan (1%).
conclusionsWithout changing their process, systematic reviewers identified issues in most RCTs that could be easily resolved by the trial authors; however, the lack of an established author feedback mechanism represents a wasted opportunity for facilitating improvement and enhancing the overall manuscript quality. On the other hand, despite the existing feedback loop to authors present in post-publication peer review, it demonstrated limited effectiveness in identifying methodological and reporting issues.
Indexed as
Identifiers
What OpenQuestion holds
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.