P539 Assessment of age as a risk factor for adverse events in patients from the tofacitinib ulcerative colitis clinical programme
Bibliographic record
Abstract
Abstract Background Tofacitinib is an oral, small-molecule JAK inhibitor for the treatment of UC. Safety and efficacy of tofacitinib were demonstrated in Phase (P)2/3 induction studies, a 52-week, P3 maintenance study, and are being further investigated in an ongoing, open-label, long-term extension (OLE) study.1,2 Here, we provide an updated analysis of age as a risk factor for adverse events (AEs) in the tofacitinib UC clinical programme.3 Methods Proportions of AEs and serious AEs (SAEs), and incidence rates (IRs; unique patients with events per 100 patient-years) for AEs of special interest (AESIs), were determined for two cohorts: the Maintenance Cohort (patients who received placebo or tofacitinib 5 or 10 mg twice daily [BID] in the maintenance study) and the Overall Cohort (all tofacitinib 5 or 10 mg BID-treated patients in the P2/P3/OLE studies; as of May 2019), stratified by age. Multivariable Cox proportional hazards regression analyses were performed to assess whether older age was associated with increased risk of AESIs in the Overall Cohort. Results In the Maintenance Cohort, IRs of AEs and SAEs were generally similar between treatment groups, with no age-related trend in the proportions of AEs in tofacitinib-treated patients. AESIs were infrequent in both treatment groups; however, herpes zoster (HZ; non-serious and serious) IRs were numerically higher in the ≥40 to <50 and ≥50 years age groups for patients treated with tofacitinib 10 mg BID vs. placebo and tofacitinib 10 vs. 5 mg BID. In the Overall Cohort, IR of serious infections was generally similar between age groups, while IRs of opportunistic infections (OIs) and HZ (non-serious and serious), malignancy (excl. non-melanoma skin cancer [NMSC]), NMSC and major adverse cardiovascular events increased with increasing age. The IRs of HZ and NMSC were significantly greater in patients ≥50 years compared with patients <30 years, and in patients ≥30 to <40 years for NMSC. In multivariate analyses, older age was identified as a significant predictor of malignancy (excl. NMSC), NMSC and HZ. Conclusion In the Overall Cohort, there was a trend for an increase in the rates of OIs, HZ, malignancy (excl. NMSC) and NMSC with increasing age. In multivariate analyses, older age was associated with increased risk of malignancy (excl. NMSC), NMSC and HZ. The results of this analysis are generally consistent with previous studies suggesting older age may be associated with an increased risk of certain AESIs in patients with UC, and in some instances in the general population.4 References
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".