Predicting Endoscopic Improvement in Ulcerative Colitis Using the Ulcerative Colitis Severity Index
Bibliographic record
Abstract
INTRODUCTION: We developed and internally validated a prognostic scoring index for ulcerative colitis (UC) patients that includes baseline patient-reported outcomes (PROs), biomarkers, endoscopy, and histology for achieving 1-year endoscopic improvement (EI). METHODS: This post hoc analysis included 644 patients treated with ustekinumab induction therapy. Data were randomly split to obtain a 70% training and 30% testing cohort. Multivariate analyses assessed baseline variables and those with P < .05 were assigned weights based on their relative prognostic value from logistic regression modeling for predicting 1-year EI (Mayo endoscopic score ≤1). A cutoff was obtained by calculating the maximum Youden index and validated in the testing cohort. RESULTS: Prior biologic failure, albumin <40 g/L, C-reactive protein >5 mg/L, Mayo stool frequency subscore, endoscopic erosions/ulcerations, and chronic histologic structural/architectural changes demonstrated significant associations with 1-year EI and were included in the final model. The Ulcerative Colitis Severity Index (UCSI) had acceptable discriminative ability for 1-year EI in the training (area under the curve [AUC], 0.78; 95% confidence interval, 0.70-0.86) and testing cohort (AUC, 0.76; 95% CI, 0.68-0.85). Compared with the UCSI, the Mayo Clinic score demonstrated poor accuracy (AUC, 0.49; 95% CI, 0.40-0.58) for predicting 1-year EI (P = .0006). The UCSI predicted 1-year endoscopic healing (Mayo endoscopic score = 0), clinical remission (total Mayo Clinic score ≤2 and no subscore >1), partial Mayo score remission <2, and 2-item Patient-Reported Outcome score (Mayo stool frequency and rectal bleeding subscore = 0) with significantly greater accuracy compared with the Mayo Clinic score. DISCUSSION: The UCSI is an internally validated prognostic scoring tool that accurately predicts 1-year EI at baseline among moderate-to-severe UC patients initiating therapy. Further validation with additional datasets is needed.
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 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".