Sex-associated Treatment Differences and Their Outcomes in Rheumatoid Arthritis: Results from the METEOR Register
Bibliographic record
Abstract
OBJECTIVE: To assess differences in initial treatment and treatment response in male and female patients with rheumatoid arthritis (RA) in daily clinical practice. METHODS: The proportion of patients with RA starting different antirheumatic treatments (disease-modifying antirheumatic drugs; DMARD) and the response to treatment were compared in the international, observational METEOR register. All visits from start of the first DMARD until the first DMARD switch or the end of followup were selected. The effect of sex on time to switch from first to second treatment was calculated using Cox regression. Linear mixed model analyses were performed to assess whether men and women responded differently to treatments, as measured by Disease Activity Score (DAS) or Health Assessment Questionnaire. RESULTS: Women (n = 4393) more often started treatment with hydroxychloroquine, as monotherapy or in combination with methotrexate (MTX) or a glucocorticoid, and men (n = 1142) more often started treatment with MTX and/or sulfasalazine. Time to switch DMARD was shorter for women than for men. Women had a statistically significantly higher DAS over time than men (DAS improvement per year β -0.69, 95% CI -0.75 to -0.62 for men and -0.58, 95% CI -0.62 to -0.55 for women). Subanalyses per DMARD group showed for the conventional synthetic DMARD combination therapy a slightly greater decrease in DAS over time in men (-0.89, 95% CI -1.07 to -0.71) compared to women (-0.59, 95% CI -0.67 to -0.51), but these difference between the sexes were clinically negligible. CONCLUSION: This worldwide observational study suggests that in daily practice, men and women with RA are prescribed different initial treatments, but there were no differences in response to treatment between the sexes.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".