Comparative Safety and Effectiveness of Vedolizumab to Tumor Necrosis Factor Antagonist Therapy for Ulcerative Colitis
Bibliographic record
Abstract
BACKGROUND & AIMS: We aimed to compare safety and effectiveness of vedolizumab to tumor necrosis factor (TNF)-antagonist therapy in ulcerative colitis in routine practice. METHODS: A multicenter, retrospective, observational cohort study (May 2014 to December 2017) of ulcerative colitis patients treated with vedolizumab or TNF-antagonist therapy. Propensity score weighted comparisons for development of serious adverse events and achievement of clinical remission, steroid-free clinical remission, and steroid-free deep remission. A priori determined subgroup comparisons in TNF-antagonist-naïve and -exposed patients, and for vedolizumab against infliximab and subcutaneous TNF-antagonists separately. RESULTS: A total of 722 (454 vedolizumab, 268 TNF antagonist) patients were included. Vedolizumab-treated patients were more likely to achieve clinical remission (hazard ratio [HR], 1.651; 95% confidence interval [CI], 1.229-2.217), steroid-free clinical remission (HR, 1.828; 95% CI, 1.135-2.944), and steroid-free deep remission (HR, 2.819; 95% CI, 1.496-5.310) than those treated with TNF antagonists. Results were consistent across subgroup analyses in TNF-antagonist-naïve and -exposed patients, and for vedolizumab vs infliximab and vs subcutaneous TNF-antagonist agents separately. Overall, there were no statistically significant differences in the risk of serious adverse events (HR, 0.899; 95% CI, 0.502-1.612) or serious infections (HR, 1.235; 95% CI, 0.608-2.511) between vedolizumab-treated and TNF-antagonist-treated patients. However, in TNF-antagonist-naïve patients, vedolizumab was less likely to be associated with serious adverse events than TNF antagonists (HR, 0.192; 95% CI, 0.049-0.754). CONCLUSIONS: Treatment of ulcerative colitis with vedolizumab is associated with higher rates of remission than treatment with TNF-antagonist therapy in routine practice, and lower rates of serious adverse events in TNF-antagonist-naïve patients.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".