Impact of Race on the Efficacy and Safety of Tofacitinib in Rheumatoid Arthritis: Post Hoc Analysis of Pooled Clinical Trials
Bibliographic record
Abstract
INTRODUCTION: Racial disparities in disease activity, clinical outcomes, and treatment survival persist despite advancements in rheumatoid arthritis (RA) therapies and clinical management. In this post hoc analysis of pooled data from the tofacitinib global clinical program, we evaluated the impact of race on the efficacy and safety of tofacitinib in patients with RA. METHODS: Data were pooled from 15 phase 2-3b/4 studies of patients with RA treated with tofacitinib 5 or 10 mg twice daily, adalimumab, or placebo. Outcomes were stratified by self-reported patient race (White/Black/Asian/Other). Efficacy outcomes to month 12 included: American College of Rheumatology (ACR)20/50/70 responses, Clinical Disease Activity Index (CDAI)/Disease Activity Score in 28 joints, erythrocyte sedimentation rate [DAS28-4(ESR)] low disease activity (LDA) rates, least squares (LS) mean change from baseline (∆) in CDAI, DAS28-4 (ESR), Health Assessment Questionnaire-Disability Index (HAQ-DI), and Pain [Visual Analog Scale (VAS)]. Odds ratios (ORs; 95% CI) versus placebo, and placebo-adjusted ∆LS means were calculated for active treatments using logistic regression model and mixed-effect model of repeated measurements, respectively. Safety outcomes were assessed throughout. RESULTS: A total of 6355 patients were included (White, 4145; Black, 213; Asian, 1348; Other, 649). For tofacitinib-treated patients, ORs for ACR20/50/70 responses and CDAI/DAS28-4(ESR) LDA rates through month 3 were generally numerically higher for White/Asian/Other versus Black patients. Across active treatments, trends toward higher placebo-adjusted improvements from baseline in CDAI, DAS28-4 (ESR), HAQ-DI, and Pain (VAS) were observed in Asian/Other versus White/Black patients. Numerically higher placebo responses in Black versus White/Asian/Other patients were generally observed across outcomes through month 12. Safety outcomes were mostly similar across treatment/racial groups. CONCLUSIONS: In patients with RA, tofacitinib was efficacious across racial groups with similar safety outcomes; observed racial differences potentially reflect patient demographics or regional practice disparities. TRIAL REGISTRATION NUMBERS: ClinicalTrials.gov identifiers: NCT00147498; NCT00413660; NCT00550446; NCT00603512; NCT00687193; NCT01164579; NCT00976599; NCT01359150; NCT00960440; NCT00847613; NCT00814307; NCT00856544; NCT00853385; NCT01039688; NCT02187055.
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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 | 0.069 | 0.074 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.023 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".