Protocol for the development of a core outcome set for clinical trials in primary sclerosing cholangitis
Bibliographic record
Abstract
BACKGROUND: Primary sclerosing cholangitis (PSC) is a progressive immune-mediated liver disease, for which no medical therapy has been shown to slow disease progression. However, the horizon for new therapies is encouraging, with several innovative clinical trials in progress. Despite these advancements, there is considerable heterogeneity in the outcomes studied, with lack of consensus as to what outcomes to measure, when to measure and how to measure. Furthermore, there has been a paradigm shift in PSC treatment targets over recent years, moving from biochemistry-based endpoints to histological assessment of liver fibrosis, imaging-based biomarkers and patient-reported outcome measures. The abundance of new interventional trials and evolving endpoints pose opportunities for all stakeholders involved in evaluating novel therapies. To this effect, there is a need to harmonise measures used in clinical trials through the development of a core outcome set (COS). METHODS AND ANALYSIS: Synthesis of a PSC-specific COS will be conducted in four stages. Initially, a systematic literature review will be performed to identify outcomes previously used in PSC trials, followed by semistructured qualitative interviews conducted with key stakeholders. The latter may include patients, clinicians, researchers, pharmaceutical industry representatives and healthcare payers and regulatory agencies, to identify additional outcomes of importance. Using the outcomes generated from the literature review and stakeholder interviews, an international two-round Delphi survey will be conducted to prioritise outcomes for inclusion in the COS. Finally, a consensus meeting will be convened to ratify the COS and disseminate findings for application in future PSC trials. ETHICS AND DISSEMINATION: Ethical approval has been granted by the East Midlands-Leicester Central Research Ethics Committee (Ref: 24/EM/0126) for this study. The COS from this study will be widely disseminated including publication in peer-reviewed journals, international conferences, promotion through patient-support groups and made available on the Core Outcomes Measurement in Effectiveness Trials (COMET) database. TRIAL REGISTRATION NUMBER: 1239.
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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 | 0.313 | 0.317 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.009 | 0.013 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.013 | 0.016 |
| Insufficient payload (model declined to judge) | 0.093 | 0.030 |
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".