Effect of Smoking on Remission Proportions Differs Between Male and Female Patients with Rheumatoid Arthritis: A Study Based on the IORRA Survey
Bibliographic record
Abstract
OBJECTIVE: To analyze sex difference in the effect of smoking on remission proportions in patients with rheumatoid arthritis (RA). METHODS: Subjects were Japanese patients with RA who participated in the IORRA survey conducted in April 2011 and reported smoking status. Clinical characteristics, treatment status, and the percentages achieving remission were compared between subjects stratified by sex and smoking status. To confirm the differential effects of sex and smoking status on remission, we used multivariate logistic regression models with the dependent variable as 28-joint Disease Activity Score (DAS28) remission. RESULTS: Among 810 men and 4206 women, 162 (20.0%) and 3173 (75.4%), respectively, were never smokers; 208 (25.7%) and 314 (7.5%), respectively, were current smokers. In men, never smokers tended to have higher remission proportions than past and current smokers. In contrast, smoking status seemed not to affect remission in women. Except for lower corticosteroid dose in male never smokers, no significant differences were observed in comparing treatment status. By multivariate analyses, male past and current smokers were negatively associated with DAS28-erythrocyte sedimentation rate remission compared to male never smokers [OR 0.66 and 0.61, 95% CI (0.44-0.98) and (0.39-0.96), respectively]. However, female past and current smokers were not associated with remission compared to female never smokers [OR 1.04 and 1.19, 95% CI (0.86-1.25) and (0.91-1.54), respectively]. CONCLUSION: We demonstrated that the effect of smoking on remission proportions differed between men and women. Our findings suggest that both sex and smoking status are important considerations when planning a treatment strategy for patients with RA.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".