170 SPIRIT-outcomes and CONSORT-outcomes: enhanced trial outcome transparency, less bias, improved systematic reviews, better health
Bibliographic record
Abstract
Objectives Clinicians, patients, and policy makers rely on published results from clinical trials to help inform evidence-based decision-making. To be able to critically evaluate and use the results of trials, readers require complete and transparent information with respect to what was planned, what was done, and what was found. Inadequate reporting of trials is well-documented in the medical literature, including for study outcomes. Key information about the selection process, definition, measurement, and analysis of outcomes is often missing or poorly reported in trial protocols and subsequent published reports. Complete reporting of the investigated trial outcomes enables reproducibility of results, knowledge synthesis efforts, and prevents outcome switching and other reporting biases - ultimately helping to facilitate uptake of trial results into clinical practice. The objective of this international project was to develop the SPIRIT- and CONSORT-Outcomes reporting guidelines to provide harmonized guidance for describing outcomes in trial protocols and reports, respectively. Method We developed the SPIRIT- and CONSORT-Outcomes reporting guidelines using the EQUATOR framework for health research reporting guidelines. This included the generation and evaluation of candidate outcome reporting items via expert consultations, a scoping review, a three-round international Delphi survey, and a two-day in-person expert Consensus Meeting. A diverse group of stakeholders was involved throughout the process including those with experience in the design, conduct, oversight, publication, and interpretation of clinical trials (e.g., trialists, biostatisticians, health economists, trial registries, research ethics board members, epidemiologists) and stakeholders who use the results of clinical trial reports (e.g. journal editors, clinicians, systematic review authors, health technology assessors). Additional stakeholders, i.e., patient and public representatives and research funders, contributed to guideline development during the Consensus Meeting. Results We identified 133 outcome reporting items from the scoping review and expert consultations, the majority of which are not currently included in CONSORT or SPIRIT reporting guidelines. Items were consolidated into 67 candidate items for Delphi voting, which was completed by 124 participants from 22 countries. After the Delphi survey, 19 items met criteria for further evaluation at the Consensus Meeting for inclusion in CONSORT-Outcomes and 30 for inclusion in SPIRIT-Outcomes. The Consensus Meeting and post-Consensus Meeting finalization process ultimately yielded 8 SPIRIT-Outcomes and 16 CONSORT-Outcomes extension items. Items focused on outcome-specific issues such as those relating to outcome definition, rationale of outcome selection, components of composite outcomes, minimal important difference and change, measurement properties of study instruments, outcome assessors, and planned adjustments for multiplicity. Conclusions The SPIRIT- and CONSORT-Outcomes reporting extensions provide harmonized recommendations for outcome-specific information that should be addressed and included in clinical trial protocols and published clinical trial reports. Use and implementation of these extensions by trial authors, peer reviewers, journals, research funders, and other end-users promises to help enhance trial utility, reproducibility, and minimize the risk of selective reporting, thus reducing research waste.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.562 | 0.643 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".