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Record W3040859129 · doi:10.1186/s13063-020-04440-w

Outcome reporting recommendations for clinical trial protocols and reports: a scoping review

2020· review· en· W3040859129 on OpenAlexafffund
Nancy J. Butcher, Emma J. Mew, Andrea Monsour, An‐Wen Chan, David Moher, Martin Offringa

Bibliographic record

VenueTrials · 2020
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsOttawa HospitalUniversity of OttawaWomen's College HospitalSickKids FoundationUniversity of TorontoInstitute for Clinical Evaluative SciencesHospital for Sick Children
FundersCanadian Institutes of Health ResearchHospital for Sick Children
KeywordsConsolidated Standards of Reporting TrialsProtocol (science)MedicineMEDLINEClinical trialOutcome (game theory)Reporting biasSystematic reviewAlternative medicineFamily medicineMedical physicsPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Clinicians, patients, and policy-makers rely on published evidence from clinical trials to help inform decision-making. A lack of complete and transparent reporting of the investigated trial outcomes limits reproducibility of results and knowledge synthesis efforts, and contributes to outcome switching and other reporting biases. Outcome-specific extensions for the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT-Outcomes) and Consolidated Standards of Reporting Trials (CONSORT-Outcomes) reporting guidelines are under development to facilitate harmonized reporting of outcomes in trial protocols and reports. The aim of this review was to identify and synthesize existing guidance for trial outcome reporting to inform extension development. METHODS: We searched for documents published in the last 10 years that provided guidance on trial outcome reporting using: an electronic bibliographic database search (MEDLINE and the Cochrane Methodology Register); a grey literature search; and solicitation of colleagues using a snowballing approach. Two reviewers completed title and abstract screening, full-text screening, and data charting after training. Extracted trial outcome reporting guidance was compared with candidate reporting items to support, refute, or refine the items and to assess the need for the development of additional items. RESULTS: In total, 1758 trial outcome reporting recommendations were identified within 244 eligible documents. The majority of documents were published by academic journals (72%). Comparison of each recommendation with the initial list of 70 candidate items led to the development of an additional 62 items, producing 132 candidate items. The items encompassed outcome selection, definition, measurement, analysis, interpretation, and reporting of modifications between trial documents. The total number of documents supporting each candidate item ranged widely (median 5, range 0-84 documents per item), illustrating heterogeneity in the recommendations currently available for outcome reporting across a large and diverse sample of sources. CONCLUSIONS: Outcome reporting guidance for clinical trial protocols and reports lacks consistency and is spread across a large number of sources that may be challenging to access and implement in practice. Evidence and consensus-based guidance, currently in development (SPIRIT-Outcomes and CONSORT-Outcomes), may help authors adequately describe trial outcomes in protocols and reports transparently and completely to help reduce avoidable research waste.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.822
metaresearch head score (Gemma)0.944
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Meta-epidemiology (broad)
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.794
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.8220.944
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0760.023
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0020.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.994
GPT teacher head0.823
Teacher spread0.171 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
DomainReporting
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations55
Published2020
Admission routes2
Has abstractyes

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