Development of interim patient-reported outcome measures for the assessment of ulcerative colitis disease activity in clinical trials
Bibliographic record
Abstract
BACKGROUND: Patient-reported outcomes (PROs) have an increasingly important role in the evaluation of new therapies for inflammatory bowel disease. The US Food and Drug Administration has issued formal guidance to describe the role of PRO instruments in evaluation of claims for product labelling. However, no validated PRO exists for ulcerative colitis. AIM: To investigate whether the PROs from the Mayo Clinic Score (MCS) for UC can be modified, to develop an interim PRO for use in clinical trials, alone or in combination with endoscopy. METHODS: Data from an induction trial of a mesalazine (mesalamine) formulation were used to compare effect sizes between mesalazine and placebo for PRO items (stool frequency and rectal bleeding) alone and in combination with endoscopy. The operating properties of the PRO were validated using data from a phase 2 trial of MLN02, a humanised antibody to the α4β7 integrin in patients with UC. RESULTS: A two-item PRO (PRO2) consisting of rectal bleeding = 0 and stool frequency ≤1 or ≤2, combined with an endoscopy subscore ≤1 yielded statistically significant differences between active drug and placebo. This combination yielded the most similar effect sizes and placebo rates for remission, compared to the primary trials. Use of PRO items alone yielded high placebo remission rates in both data sets, although rates were lower when the items were combined and remission defined as PRO2 = 0. CONCLUSION: Patient-reported outcomes items derived from the Mayo Clinic Score combined with endoscopy as a co-primary endpoint may be an appropriate interim outcome measure for ulcerative colitis trials.
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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 | 0.463 | 0.524 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.013 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".