Improving outcome reporting in clinical trial reports and protocols: study protocol for the Instrument for reporting Planned Endpoints in Clinical Trials (InsPECT)
Bibliographic record
Abstract
BACKGROUND: Inadequate and poor quality outcome reporting in clinical trials is a well-documented problem that impedes the ability of researchers to evaluate, replicate, synthesize, and build upon study findings and impacts evidence-based decision-making by patients, clinicians, and policy-makers. To facilitate harmonized and transparent reporting of outcomes in trial protocols and published reports, the Instrument for reporting Planned Endpoints in Clinical Trials (InsPECT) is being developed. The final product will provide unique InsPECT extensions to the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) and CONSORT (Consolidated Standards of Reporting Trials) reporting guidelines. METHODS: The InsPECT SPIRIT and CONSORT extensions will be developed in accordance with the methodological framework created by the EQUATOR (Enhancing the Quality and Transparency of Health Research Quality) Network for reporting guideline development. Development will consist of (1) the creation of an initial list of candidate outcome reporting items synthesized from expert consultations and a scoping review of existing guidance for reporting outcomes in trial protocols and reports; (2) a three-round international Delphi study to identify additional candidate items and assess candidate item importance on a 9-point Likert scale, completed by stakeholders such as trial report and protocol authors, systematic review authors, biostatisticians and epidemiologists, reporting guideline developers, clinicians, journal editors, and research ethics board representatives; and (3) an in-person expert consensus meeting to finalize the set of essential outcome reporting items for trial protocols and reports, respectively. The consensus meeting discussions will be independently facilitated and informed by the empirical evidence identified in the primary literature and through the opinions (aggregate rankings and comments) collected via the Delphi study. An integrated knowledge translation approach will be used throughout InsPECT development to facilitate implementation and dissemination, in addition to standard post-development activities. DISCUSSION: InsPECT will provide evidence-informed and consensus-based standards focused on outcome reporting in clinical trials that can be applied across diverse disease areas, study populations, and outcomes. InsPECT will support the standardization of trial outcome reporting, which will maximize trial usability, reduce bias, foster trial replication, improve trial design and execution, and ultimately reduce research waste and help improve patient outcomes.
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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 | 0.568 | 0.683 |
| Meta-epidemiology (narrow) | 0.007 | 0.010 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.015 | 0.024 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.020 | 0.037 |
| Insufficient payload (model declined to judge) | 0.042 | 0.038 |
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".