Abstract P185: Adverse Cardiovascular Events In Patients With Psoriasis And Psoriatic Arthritis
Bibliographic record
Abstract
Background: Patients with psoriasis who have severe enough disease to require biologic therapy have increased risk of cardiovascular (CV) disease and CV comorbidities. Complications of immune modulating therapy can include weight and lipid alterations, potentiation of heart failure, and athero or venoembolic events, which may also be race or gender dependent. Clinical trials of biologic therapy represent an opportunity to capture and study CV related events and important safety signals. The aim of this investigation was to evaluate the public reporting of CV related adverse events in the psoriatic patient population. Methods: The prevalence of reporting of demographics, and adverse CV related events was obtained from clinicaltrials.gov from registered clinical trials leading to FDA approval of biologic medications. Results: In total, 39 clinical trials of biologic therapy ranging from 2011 through 2020 were included encompassing 27,693 participants. Median age was 46 (IQR; 45 - 48) years and 68% (IQR; 48 - 69) male. Nineteen (49%) of the trials reported race, of which whites constituted 89% (range 67 - 98) of the enrolled population. Randomization of Blacks (median 2.3%, range 0 - 3.9) and Hispanics (median 10.3%, range 0.3 - 17) was low. Thirty-two of 39 (82%) of trials reported acute coronary syndrome as a serious adverse event. Other adverse cardiovascular endpoints were less frequently reported (Figure 1). Conclusion: There is significant underreporting of minority populations in clinical trials of biologics in patients with psoriasis. When reported, there is low representation of minority groups. Furthermore, adverse event reporting of CV disease is poor and inconsistent. These data represent a missed opportunity to study important safety signals in this high CV risk patient population across a diverse generalizable 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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".