<i>Clostridium difficile</i> Infection in Patients with Ulcerative Colitis Treated with Tofacitinib in the Ulcerative Colitis Program
Bibliographic record
Abstract
BACKGROUND: Tofacitinib is an oral, small molecule Janus kinase inhibitor for the treatment of ulcerative colitis (UC). Patients with inflammatory bowel disease are susceptible to Clostridium difficile infection (CDI). Here, we evaluate CDI in the tofacitinib UC clinical program. METHODS: Events from 4 randomized, placebo-controlled studies (phase [P] 2 or P3 induction [NCT00787202; NCT01465763; NCT01458951], P3 maintenance [NCT01458574]) and an open-label, long-term extension (OLE) study (NCT01470612), were analyzed as 3 cohorts: Induction (P2/P3 induction), Maintenance (P3 maintenance), and Overall (patients receiving tofacitinib 5 or 10 mg twice daily [BID] in P2, P3, and OLE studies; including final data from the OLE study, as of August 24, 2020). Proportions and incidence rates (unique patients with events per 100 patient-years of exposure) of CDI were evaluated. RESULTS: The overall cohort comprised 1157 patients who received ≥1 dose of tofacitinib 5 or 10 mg BID, with a total of 2814.4 patient-years of tofacitinib exposure and up to 7.8 years of treatment. A total of 82.6% of patients received predominantly tofacitinib 10 mg BID. In the induction, maintenance, and overall cohorts, 3 (2 tofacitinib treated, 1 placebo treated), 3 (all placebo treated), and 9 patients had CDI, respectively; the overall cohort incidence rate was 0.31 (95% confidence interval, 0.14-0.59). CDI were all mild-moderate in severity and resolved with treatment in 8 patients. Six of 9 patients continued tofacitinib treatment without interruption. Two patients had events reported as serious due to hospitalization. Two patients were receiving corticosteroids when the CDI occurred. CONCLUSION: CDIs among patients with UC receiving tofacitinib were infrequent, cases were mild-moderate in severity, and most resolved with treatment.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".