Assessment of Safety and Efficacy of Tofacitinib, Stratified by Age, in Patients from the Ulcerative Colitis Clinical Program
Bibliographic record
Abstract
BACKGROUND: In patients with ulcerative colitis (UC), risks of infection and malignancies increase with age. Tofacitinib is an oral, small molecule Janus kinase inhibitor for the treatment of UC. This analysis assessed age as a risk factor for adverse events of special interest (AESI) in the tofacitinib UC clinical program. METHODS: Data were from phase 2 and 3 induction studies, a phase 3 maintenance study, and an open-label, long-term extension study. Efficacy and/or safety outcomes were analyzed in the Induction, Maintenance, and Overall Cohorts (patients who received ≥ 1 dose of tofacitinib), stratified by age. The effects of baseline demographic and disease-related factors on AESI incidence were assessed by Cox proportional-hazards regression analysis. RESULTS: In the Overall Cohort (1157 patients with ≤ 6.8 years' tofacitinib treatment), age was a statistically significant predictor of herpes zoster (HZ), malignancies excluding nonmelanoma skin cancer (NMSC), and NMSC. Other statistically significant predictors included prior tumor necrosis factor inhibitor failure for HZ, NMSC, and opportunistic infection events, and prior duration of UC for malignancies excluding NMSC. In the Induction and Maintenance Cohorts, a higher proportion of tofacitinib-treated than placebo-treated patients (numerical difference) achieved the efficacy endpoints (endoscopic improvement, clinical remission, clinical response) across all age groups. CONCLUSIONS: Older individuals receiving tofacitinib as induction and maintenance therapy to treat UC may have an increased risk of HZ, malignancies (excluding NMSC), and NMSC versus similarly treated younger patients, consistent with findings from the general population. Across all age groups, tofacitinib demonstrated greater efficacy than placebo as an induction and maintenance therapy. CLINICALTRIALS.GOV REGISTRATION NUMBERS: NCT00787202; NCT01465763; NCT01458951; NCT01458574; NCT01470612.
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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) | 0.001 | 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 | 0.001 |
| 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".