Exploring Weight Trends in Psoriatic Arthritis: Unraveling Effects of Drugs
Bibliographic record
Abstract
Objectives We aimed to study the change in weight with the use of csDMARDs, biologic (b) DMARDs, Janus kinase inhibitors (JAKi), and apremilast and factors affecting weight in psoriatic arthritis (PsA). Methods Patients receiving NSAIDs or no medications, conventional synthetic (cs)DMARDs only (with or without NSAIDs), TNFi as the first biologic, Interleukin (IL)-12/23i, IL17i, IL23i, JAKi, and apremilast with 2 or more weight readings over follow-up were identified from the database of a large cohort. The change in the trend of weight gain before and after was studied by adjusting for age, sex, disease duration, comorbidities, disease activity (Psoriasis Area and Severity Index [PASI] and swollen joint count [SJC]), line of treatment, and smoking using linear mixed-effect modeling for those with 2 weight readings available before and after starting the drug. Factors affecting weight over time for the cohort were studied using another linear mixed model adjusting for the above factors along with baseline weight and all drugs received. Results A total of 1754 patients were included with 473 patients on NSAIDs or no medications, 571 on csDMARDs, 702 on bDMARDs, 42 on JAKi, and 70 on apremilast. The age at baseline, onset of psoriasis, and PsA were lower in the bDMARD group. Baseline weight, proportion with hypertension, PASI, and DAPSA scores were higher in the apremilast group. The proportion with HLA-C6 was the highest in the NSAIDs or no medication group. On change point analysis comparing the mean weight slopes before and after medication use, significant weight loss was observed with IL17i (p<0.001), IL23i (p=0.002), and csDMARDs (p<0.001) whereas the weight change was not significant with TNFi, IL12/23i, and apremilast. However, a trend toward weight gain was observed with TNFi and weight loss with apremilast (Figure 1). When factors influencing weight were compared across the cohort, weight gain was observed with TNFi, longer duration of follow-up, higher baseline weight, hypertension, and male sex. The use of apremilast, older age, and diabetes mellitus were associated with weight loss. Conclusion Significant weight loss was observed after initiation of IL17i, IL23i, and csDMARDs in PsA as compared to weight before initiation of these drugs. However, when overall effects on weight were studied, the use of TNFi was associated with weight gain whereas apremilast was associated with weight loss.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".