Post-Marketing Safety Surveillance of Tofacitinib over 9 Years in Patients with Psoriatic Arthritis and Rheumatoid Arthritis
Bibliographic record
Abstract
INTRODUCTION: The safety of tofacitinib in psoriatic arthritis (PsA) and rheumatoid arthritis (RA) has been demonstrated in clinical studies of ≤ 4 and 9.5 years, respectively. Post-marketing surveillance (PMS) data for tofacitinib from spontaneous and voluntary adverse event (AE) reports have been published for RA, but not PsA. To inform the real-world safety profile of tofacitinib in PsA, we evaluated AE reports submitted to the Pfizer safety database (including RA data for context). METHODS: Endpoints included AEs, serious AEs (SAEs), AEs of special interest (AESIs; serious infections, herpes zoster, cardiovascular events, malignancies, venous thromboembolism), and fatal cases. Exposure was estimated using IQVIA global commercial sales data. Number, frequency, and reporting rates (RRs; number of events/100 patient-years' [PY] exposure) were summarized by indication and formulation (immediate release [IR] 5 or 10 mg twice daily], modified release [MR] 11 mg once daily, or all tofacitinib). The data-collection period differed by indication (PsA: 14 December 2017 [US approval, IR/MR] to 6 November 2021; RA: 6 November 2012 [US approval, IR] to 6 November 2021; MR approval, 24 February 2016). RESULTS: A total of 73,525 case reports were reviewed (PsA = 5394/RA = 68,131), with 20,706/439,370 PY (PsA/RA) of exposure. More AEs were reported for IR versus MR (IR/MR: PsA = 8349/7602; RA = 137,476/82,153). RRs for AEs (IR/MR: PsA = 59.6/113.4; RA = 44.0/64.8) and SAEs (PsA = 8.1/13.6; RA = 8.0/9.5) were higher with MR versus IR. AE RRs (RA) in the first 4 years after IR approval were 95.9 (IR; 49,439 PY) and 147.0 (MR; 2000 PY). Frequency of SAEs, AESIs, and fatal cases was mostly similar across formulations and indications. The most frequently-reported AE Preferred Terms (PsA/RA) included drug ineffective (20.0%/17.8%), pain (9.7%/10.6%), condition aggravated (9.9%/10.5%), headache (8.8%/7.9%) and, for PsA, off-label use (10.5%/3.4%). CONCLUSIONS: Tofacitinib PMS safety data from submitted AE reports were consistent between PsA and RA, and aligned with its known safety profile. Exposure data (lower MR versus IR; estimation from commercial sales data), reporting bias, reporter identity, and regional differences in formulation use limit interpretation.
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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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".