Postapproval Comparative Safety Study of Tofacitinib and Biological Disease‐Modifying Antirheumatic Drugs: 5‐Year Results from a United States–Based Rheumatoid Arthritis Registry
Bibliographic record
Abstract
OBJECTIVE: Tofacitinib is an oral Janus kinase inhibitor for the treatment of rheumatoid arthritis (RA). We compared 5-year adverse event (AE) incidence rates (IRs) between patients initiating tofacitinib and those initiating new biological disease-modifying antirheumatic drugs (bDMARDs) within the United States (US) Corrona RA registry. METHODS: IRs (number of first events/100 patient-years) of major adverse cardiovascular events (MACE), serious infection events (SIEs), herpes zoster (HZ), malignancies, and death were estimated among tofacitinib and bDMARD initiators, regardless of dose/schedule, between November 6, 2012 (US Food and Drug Administration tofacitinib approval), and July 31, 2018 (follow-up through January 31, 2019). Propensity score (PS) methods were used to control for nonrandom prescribing practices. Hazard ratios (HRs) were calculated to compare rates using multivariable-adjusted Cox regression. Different risk windows were used for acute (MACE, SIEs, HZ, and venous thromboembolic events [VTEs]) and long-term (malignancy and death) events. VTEs were assessed descriptively. RESULTS: For MACE, SIEs, and HZ, 1999 (3152.1 patient-years) and 8358 (12 869.4 years) tofacitinib and bDMARD initiators were included, respectively; for malignancy/death, 1999 (4505.6 patient-years) and 6354 (16 670.8 patient-years) initiators were included, respectively. AE rates were similar across cohorts, except for HZ, which was significantly higher with tofacitinib versus bDMARDs (PS-trimmed adjusted HR 2.32; 95% confidence interval [CI] 1.43-3.75). There were 45 (zero serious) and 88 (five serious) HZ events with tofacitinib and bDMARDs, respectively. Sensitivity analyses demonstrated similar results. VTE IRs (95% CI) were 0.29 (0.13-0.54) and 0.33 (0.24-0.45) for tofacitinib and bDMARDs, respectively. CONCLUSION: In this registry analysis, both cohorts had similar MACE, SIE, malignancy, death, and VTE rates; HZ rates were higher for tofacitinib initaitors than for bDMARD initiators.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".