Long-term tofacitinib efficacy and safety in psoriatic arthritis with or without prior biologic DMARD exposure: a post hoc analysis
Bibliographic record
Abstract
Objective: To assess long-term tofacitinib efficacy and safety in patients with PsA with or without prior biologic DMARD (bDMARD) exposure. Methods: Data were pooled post hoc from three phase 3 and one long-term extension (LTE) PsA studies and stratified by TNF inhibitor-inadequate responder (TNFi-IR) or bDMARD-naïve patient status at the phase 3 study baseline. Data were reported as all tofacitinib (patients receiving one or more tofacitinib doses) or average tofacitinib 5 and 10 mg twice daily (patients receiving an average total daily dose <15 and ≥15 mg, respectively). Drug survival to month 51, efficacy to month 42 and safety were assessed descriptively. Results: bDMARD-naïve patients, treatment-emergent adverse event incidence rates were higher and serious adverse event, serious infection and herpes zoster incidence rates were numerically higher (CI overlapped). Conclusion: These findings support long-term tofacitinib efficacy and safety in TNFi-IR and bDMARD-naïve patients. However, the benefit-risk profile appeared more favourable in bDMARD-naïve patients, likely due to differences in baseline characteristics and risk factors between subgroups. Trial registration: ClinicalTrials.gov: NCT01877668, NCT01882439, NCT03486457, NCT01976364.
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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 | 0.014 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.013 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".