Choice of Biologic Immunotherapy for Psoriasis or Psoriatic Arthritis and Its Association With Risk of Major Adverse Cardiac Events
Bibliographic record
Abstract
OBJECTIVE: Individuals with psoriasis (PsO) or psoriatic arthritis (PsA) have an elevated risk of major adverse cardiac events (MACE), which include congestive heart failure (CHF), myocardial infarction (MI), and cerebrovascular accident (CVA). Biologic disease-modifying antirheumatic drugs (bDMARDs) may reduce cardiovascular risk; however, whether MACE risk differs by bDMARD class for this population is unknown. METHODS: Using data from TriNetX database, we identified patients with PsO/PsA who were new bDMARD users, including tumor necrosis factor inhibitors (TNFi), interleukin (IL)-17A inhibitors (-i), IL-23i, or IL-12/23i. Time-dependent risk for MACE was calculated using weighted multinomial Cox proportional hazards regression with TNFi exposure as the referent. Additional analyses evaluated components of the primary outcome and baseline cardiovascular disease. A negative control outcome was used to assess bias. RESULTS: We identified 32,758 patients with PsO/PsA who were new bDMARD users. Patients had PsO/PsA for a mean of 3.5 (SD 4.5) years prior to starting a biologic, the most common being TNFi (62.9%), followed by IL-17i (15.4%), IL-23i (11%), and IL-12/23i (10.7%). In weighted multinomial Cox proportional hazards regression, the adjusted risk of MACE was similar for IL-17Ai (adjusted hazard ratio [aHR] 0.98, 95% CI 0.73-1.32), IL-23i (aHR 0.84, 95% CI 0.54-1.31), and IL-12/23i (aHR 1.08, 95% CI 0.80-1.47) as compared to TNFi. Subset analyses supported the primary analysis. Negative control outcomes suggested adequate control of bias confounding. CONCLUSION: MACE risk does not significantly differ across bDMARD classes in patients with PsO/PsA. Therefore, cardiovascular risk should not guide biologic selection in this population.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".