Diagnostic accuracy of patient‐reported outcomes in predicting endoscopic subscore in patients with ulcerative colitis
Bibliographic record
Abstract
Background Tofacitinib is an oral, small molecule Janus kinase inhibitor for the treatment of ulcerative colitis (UC). In patients with UC, associations between endoscopic findings and UC symptoms are not well described. Aims Post hoc analysis of data from two randomised, placebo-controlled, 8-week, phase 3 studies of tofacitinib for the treatment of patients with UC. Methods Associations of stool frequency and rectal bleeding subscores with endoscopic improvement (Mayo endoscopic subscore ≤1) were assessed and relationships studied using regression analyses. Results Analysis of two-by-two contingency tables showed that dichotomised stool frequency and rectal bleeding were each or both not good predictors of endoscopic improvement. Using stool frequency and/or rectal bleeding as predictors of endoscopic subscore, regression modelling analyses demonstrated a weak relationship between variables. However, a robust relationship was observed with endoscopic subscore as a predictor of stool frequency and rectal bleeding. In OCTAVE Induction 1, normal/inactive disease (endoscopic subscore 0) corresponded to a least-squares mean value of 0.05 for rectal bleeding (no blood), and severe disease (endoscopic subscore 3) corresponded to a value of 1.5 (interpreted as streaks of blood with stool <50% of the time [score of 1] or obvious blood with stool most of the time [score of 2]). OCTAVE Induction 2 results were similar. Conclusions Results suggest that the likelihood of endoscopic improvement or normalisation is higher in patients with normal stool frequency and without rectal bleeding, but that these symptoms alone are not predictive of endoscopic improvement or normalisation, and endoscopy is needed for disease assessment. ClinicalTrials.gov: NCT01465763; NCT01458951.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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; a candidate call from one teacher head, not a consensus.
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".