Association of Tumor Necrosis Factor Inhibitor Treatment With Reduced Indices of Subclinical Atherosclerosis in Patients With Psoriatic Disease
Bibliographic record
Abstract
Objective To assess the effect of tumor necrosis factor inhibitors (TNFi) on subclinical cardiovascular disease in patients with psoriatic disease. Methods We performed a 2‐stage study. In stage 1, carotid total plaque area was assessed in patients with psoriasis or psoriatic arthritis (PsA) (n = 319) by ultrasound at baseline and after 2–3 years. The annual progression rate of atherosclerosis was the outcome of interest. In stage 2, PsA patients receiving TNFi (n = 21) and age‐ and sex‐matched PsA patients not receiving any biologic agent (n = 13) underwent 18F‐fluorodeoxyglucose–positron emission tomography/computed tomography at baseline and 1 year to assess vascular inflammation, measured as target‐to‐background ratio (TBR). In both stages, multivariable regression analyses adjusted for cardiovascular risk factors and use of statins were performed. Results In stage 1, men had significantly higher atherosclerosis progression than women (P < 0.001). TNFi was associated with reduced atherosclerosis progression in men after controlling for cardiovascular risk and use of statins (adjusted β = −2.20 [95% confidence interval −3.41, −1.00], P < 0.001). There was no association between TNFi and atherosclerosis progression in women (P = 0.74). In stage 2, patients receiving TNFi had reduced TBR at 1 year (P = 0.03). Those not receiving TNFi had no significant change in TBR (P = 0.32). The improvement in aortic vascular inflammation in the TNFi group was independent of cardiovascular risk factors (adjusted β = −0.41 [95% confidence interval −0.74, −0.08], P = 0.02). Conclusion Our findings indicate that TNFi treatment is associated with reduced progression of carotid plaques in men and improvement in vascular inflammation in both men and women with psoriatic disease.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".