Comparative Speed of Early Symptomatic Remission With Advanced Therapies for Moderate-to-Severe Ulcerative Colitis: A Systematic Review and Network Meta-Analysis
Bibliographic record
Abstract
INTRODUCTION: Rapidity of symptom resolution informs treatment choice in patients with moderate-severe ulcerative colitis (UC). We conducted a systematic review and network meta-analysis comparing early symptomatic remission with approved therapies. METHODS: Through a systematic literature review to December 31, 2022, we identified randomized trials in adult outpatients with moderate-severe UC treated with approved therapies (tumor necrosis factor α antagonists, vedolizumab, ustekinumab, janus kinase inhibitors, or ozanimod), compared with each other or placebo, reporting rates of symptomatic remission (based on partial Mayo score, with resolution of rectal bleeding and near-normalization of stool frequency) at weeks 2, 4, and/or 6. We performed random-effects network meta-analysis using a frequentist approach and estimated relative risk (RR) and 95% confidence interval values. RESULTS: On network meta-analysis, upadacitinib was more effective than all agents in achieving symptomatic remission at weeks 2 (range of RR, 2.85-6.27), 4 (range of RR, 1.78-2.37), and 6 (range of RR, 1.84-2.79). Tumor necrosis factor α antagonists and filgotinib, but not ustekinumab and vedolizumab, were more effective than ozanimod in achieving symptomatic remission at week 2, but not at weeks 4 and 6. With approximately 10% placebo-treated patients achieving symptomatic remission at 2 weeks, we estimated 68%, 22%, 23.7%, 23.9%, 22.2%, 18.4%, 15.7%, and 10.9% of upadacitinib-, filgotinib-, infliximab-, adalimumab-, golimumab-, ustekinumab-, vedolizumab-, and ozanimod-treated patients would achieve early symptomatic remission, ustekinumab and vedolizumab achieving rapid remission only in biologic-naïve patients. DISCUSSION: In a systematic review and network meta-analysis, upadacitinib was most effective in achieving early symptomatic remission, whereas ozanimod was relatively slower acting.
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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 | 0.028 | 0.061 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.040 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".