P1084 Safety of tofacitinib and upadacitinib compared to other advanced therapies in ulcerative colitis: a large real-world comparison
Bibliographic record
Abstract
Abstract Background Whether adverse events of special interest[1] related to JAK inhibitors (JAKi) are a concern compared to other drugs used in ulcerative colitis (UC) needs investigation. We aimed to assess and compare the frequency of adverse events of special interest by JAKi within the class, and with other advanced therapies, on a large real-world population of UC patients. Methods This was a non-interventional, retrospective study conducted with data obtained from TriNetX from patients with diagnosis of adult UC, exposed to advanced therapies (range 1-1095 days). The final cohort included 866 patients over 444,424 UC patients available in the database who matched the query criteria. Adverse events (any), herpes zoster, cardiovascular events, thromboembolic events, cancer (any), non-melanoma skin cancer were investigated. We compared each JAKi with TNF, IL-23 antagonists, and vedolizumab, and within the class by survival analyses and log-rank test. Propensity score matching and adjustment for confounders, such as age, sex, first or second line advanced therapy, smoking habit and other known baseline risk factors, was done. Statistical significance was set as a p value < 0.05. Results Only tofacitinib and upadacitinib were included, as data on filgotinib were not available. Tofacitinib was associated with statistically significant lower rates of thromboembolic events than anti-TNFs (HR 0.61, 95% CI 0.38-098, p=0.04), and lower rates of cancer than vedolizumab (HR 0.63, 95% CI 0.41-0.96, p=0.03), but higher rates of herpes zoster than anti-IL23 (p=0.001). Upadacitinib showed lower rates of thromboembolic events (p=0.001), but higher rates of herpes zoster reactivation than IL-23 (p=0.001). Similar safety profile was found between tofacitinib and upadacitinib when they were directly compared. Conclusion Anti-JAK show a similar safety profile than all the other drug classes used in UC. Herpes zoster infection/reactivation remains the only adverse event of note for both JAKi. References 1.European Medicine Agency. EMA recommends measures to minimise risk of serious side effects with Janus kinase inhibitors for chronic inflammatory disorders. 2022 [cited 2024 Jun 12]; Available from: https://www.ema.europa.eu/en/news/ema-recommends-measures-minimise-risk-serious-side-effects-janus-kinase-inhibitors-chronic-inflammatory-disorders.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".