Real-world Clinical Effectiveness and Safety of Vedolizumab and Adalimumab in Biologic-naive Patients With Crohn’s Disease
Bibliographic record
Abstract
GOALS: This study evaluated the real-world effectiveness and safety of vedolizumab versus adalimumab over 12 months of treatment in biologic-naive patients with Crohn's disease (CD), using data from the EVOLVE study. BACKGROUND: A comparison of vedolizumab and adalimumab may help to better position them in the therapeutic algorithm for moderate-to-severe CD. STUDY: Data were collected from medical records of patients with CD aged ≥18 years initiating treatment with adalimumab or vedolizumab between May 2014 and July 2017. Adjusted analyses were performed using inverse probability weighting to account for differences in baseline characteristics. Cumulative rates for clinical effectiveness outcomes and treatment persistence were estimated using Kaplan-Meier analyses. Disease-related exacerbations, serious adverse events (SAEs), and serious infections (SIs) were also assessed. RESULTS: Data from 218 vedolizumab- and 144 adalimumab-treated patients were analyzed. Adjusted cumulative rates of clinical remission were greater with vedolizumab than with adalimumab (66.3% vs. 46.4%; P =0.006). Probability of treatment persistence was higher with vedolizumab (89.3% vs. 77.5%; P =0.024); probabilities of clinical response (68.5% vs. 61.1%; P =0.586) and mucosal healing (67.7% vs. 56.0%; P =0.562) were similar. SAEs were less likely to occur with vedolizumab [hazard ratio, 0.45 (95% confidence interval, 0.22-0.93)]; however, the likelihood of SIs [0.27 (0.06-1.20)], CD exacerbations [0.91 (0.56-1.47)], and CD-related surgeries [1.55 (0.21-11.15)] was comparable between the 2 groups. CONCLUSIONS: In a real-world setting, biologic-naive patients with CD treated with vedolizumab demonstrated a greater likelihood of drug persistence and achieving clinical remission, with equivalent rates of response and mucosal healing versus adalimumab-treated 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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".