Effects of the Tumor Necrosis Factor-α Antagonist Adalimumab on Arterial Inflammation Assessed by Positron Emission Tomography in Patients With Psoriasis
Bibliographic record
Abstract
BACKGROUND: Psoriasis is a chronic inflammatory disease associated with increased risks of myocardial infarction and stroke. Systemic treatments for moderate to severe psoriasis can reduce skin and joint inflammation; however, their effects on vascular inflammation are unknown. METHODS AND RESULTS: This randomized, controlled trial included 30 patients with moderate to severe psoriasis and a history, or multiple risk factors, of coronary atherosclerosis. Patients were randomized (2:1) to receive either adalimumab subcutaneously for 4 months or to control nonsystemic treatment (topical therapies or phototherapy). Vascular inflammation was measured in the carotid artery and ascending aorta at baseline and week 15, by (18)F-fluorodeoxyglucose uptake on positron emission tomography. The change in target: BACKGROUND: =0.004) but not for the control group (-0.10 [95% CI, -0.32 to 0.12]; P=0.35). The difference between study arms for this primary end point did not reach statistical significance (-0.13 [95% CI, -0.01 to 0.14]; P=0.32). The change in target: BACKGROUND: =0.021) and in carotid arteries (-0.32±0.15, P=0.037) when analyzed separately (secondary end points). Changes in other positron emission tomography indices also improved significantly with adalimumab compared with controls in the ascending aorta and carotids. High-sensitivity C-reactive protein decreased by 51% at week 16 with adalimumab compared with 5% in controls (P=0·002). CONCLUSIONS: The study did not meet its primary end point because the change in target:background ratio in patients randomized to adalimumab was not different from controls. Although adalimumab may reduce vascular inflammation in patients with moderate to severe psoriasis, this effect is not large enough to be demonstrated in a study with a small sample size. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00940862.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".