DOP73 Predicting endoscopic improvement in Ulcerative Colitis using the Ulcerative Colitis Severity Index (UCSI)
Bibliographic record
Abstract
Abstract Background Scoring indices used in clinical trials for moderate-severe ulcerative colitis (UC) may lack specificity as a prognostic tool. We developed and internally validated a prognostic scoring index for UC patients on therapy that considers baseline patient-reported outcomes, biomarkers, endoscopy, and histology for achieving one-year endoscopic improvement (EI). Methods This post-hoc analysis of the UNIFI clinical trial (ClinicalTrials.gov identifier: NCT02407236) included 644 patients treated with ustekinumab induction therapy. Data were randomly split into 70% training and 30% testing cohorts. Baseline variables were assessed in multivariate analyses and variables with p <0.05 were assigned weights according to their relative prognostic value for predicting one-year EI (Mayo endoscopic score (MES) ≤1). A cut-off was obtained by calculating the maximum Youden index and validated in the testing cohort. Results Prior biologic failure, albumin < 40 g/L, CRP > 5mg/L, Mayo stool frequency (SF) subscore, endoscopic erosions/ulcerations based on the UC Endoscopic Index of Severity, and histologic structural/architectural changes demonstrated significant associations with one-year EI and included in the final model. The Ulcerative Colitis Severity Index (UCSI) was generated (Table 1) and the median UCSI score among all participants was 10.4 (IQR 7-14.4, range: 2.2-20), which had acceptable discriminative ability for one-year EI in the training [AUC: 0.78 (95% CI: 0.70-0.86)] and testing cohort [AUC: 0.76 (95% CI: 0.68-0.85)] (Table 2). Compared to the UCSI, the Mayo score demonstrated poor accuracy [AUC: 0.49 (95% CI: 0.40-0.58)] for predicting one-year EI (p=0.0006). The UCSI also predicted one-year endoscopic healing (MES of 0), clinical remission (total Mayo score ≤2 and no subscore >1), partial Mayo score (PMS) remission (PMS < 2), and PRO-2 remission (SF and rectal bleeding subscore of 0) with significantly greater accuracy compared to the Mayo score. Similar findings were observed when the UCSI was compared with the adapted Mayo score. The maximum Youden index corresponded to a cut-off of 10. Participants with a UCSI ≥10 had a lower probability of one-year EI [27/104 (26%) vs. 40/76 (52.6%)]. Performance characteristics are detailed in Tables 3 and 4. Conclusion The UCSI is an internally validated prognostic scoring tool that accurately predicts one-year EI at baseline among patients with moderate-to-severe UC on active therapy. The UCSI demonstrated greater accuracy for one-year EI, EH, and clinical remission compared to the total and adapted Mayo score. The UCSI could improve disease management in UC by stratifying patients based on their predicted likelihood of long-term 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".