Ulcerative Colitis Patients Continue to Improve Over the First Six Months of Vedolizumab Treatment: 12-Month Clinical and Mucosal Healing Effectiveness
Bibliographic record
Abstract
Abstract Background Vedolizumab (VDZ) is a humanized monoclonal IgG1 antibody which inhibits leukocyte vascular adhesion and migration into the gastrointestinal tract through α4β7 integrin blockade. Aims We retrospectively assessed the 12-month, real-world efficacy and safety of VDZ as induction and maintenance therapy in adult patients with ulcerative colitis (UC). Methods The rates of clinical remission (CR, partial Mayo score < 2), steroid-free clinical remission (SFCR), and mucosal healing were assessed with nonresponder imputation analysis. Baseline independent predictors of clinical remission were investigated, and adverse events were recorded. Results We analyzed outcomes in 74 patients; 32% were anti-TNF naïve, 68% had pancolitis, and 46% were on systemic steroids at baseline. At week six, week 14, six months and one year, the CR rates were 26%, 34%, 39% and 39% respectively, and the SFCR rates were 24%, 31%, 38% and 39%, respectively. Among patients not in CR after induction, the probability of remission at six months was 20%. Sustained SFCR between weeks 14 and 52 and between weeks 22 and 52 was found in 69% and 86% of the patients, respectively. Steroid-free clinical remission at 12 months was significantly associated with remission after the induction phase (OR = 30.4; 95% CI, 6 to 150; P < 0.001). Mucosal healing rate at one year was 39%. The most common side effect was headache (7%). Conclusions Increasing remission rates were observed over the first six months of VDZ treatment. One-fifth of patients not in remission post-induction achieved remission by six months of continued therapy. Mucosal healing was associated with higher rates of one-year steroid-free remission and VDZ treatment continuation.
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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 | 0.005 |
| 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 | 0.000 | 0.000 |
| 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".