Potential Impact of Sex and BMI on Response to Therapy in Psoriatic Arthritis: Post Hoc Analysis of Results From the SEAM-PsA Trial
Bibliographic record
Abstract
Objective In this post hoc analysis, we examined the potential impact of sex and BMI on response in the Study of Etanercept and Methotrexate in Combination or as Monotherapy in Subjects with Psoriatic Arthritis (SEAM-PsA) trial ( NCT02376790 ), a 48-week, phase III, randomized controlled trial that compared outcomes with methotrexate (MTX) monotherapy, etanercept (ETN) monotherapy, and MTX+ETN combination therapy in patients with psoriatic arthritis (PsA) who were naïve to MTX and biologics. Methods We evaluated key outcomes at week 24 stratified by sex (male vs female) and BMI (kg/m2; ≤ 30 vs > 30), including the American College of Rheumatology 20 (ACR20) criteria, minimal disease activity (MDA), very low disease activity (VLDA), and Psoriatic Arthritis Disease Activity Score (PASDAS). We analyzed data using descriptive statistics, normal approximation, logistic model, and analysis of covariance. Results A total of 851 patients completed the SEAM-PsA trial. Higher proportions of men than women who received MTX+ETN combination therapy achieved ACR20 (71.5% vs 58.3%;P= 0.02), MDA (45.8% vs 25.2%;P= 0.0003), and VLDA (19.1% vs 9.5%;P= 0.03), and men achieved better PASDAS (-3.0 vs -2.3;P= 0.0004). Patients with BMI ≤ 30 generally had better outcomes than those with BMI > 30 in some treatment arms for ACR20, MDA, VLDA, and PASDAS; however, there was no consistent pattern regarding the treatment arm in which the difference occurred. Conclusion Improved outcomes were observed more in men than in women for MDA and PASDAS with MTX+ETN combination therapy. Patients with BMI ≤ 30 had better outcomes than those with BMI > 30, with no clear pattern regarding treatment received. These findings suggest that contextual factors such as sex and BMI may affect response to PsA therapy.
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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 | 0.019 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".