Regional differences in cardiovascular status and events in prostate cancer patients treated with a gonadotrophin-releasing hormone agonist vs antagonist: Results of a pooled analysis.
Bibliographic record
Abstract
e16096 Background: Androgen deprivation therapy (ADT) for advanced prostate cancer (PCa) may increase the risk of cardiovascular (CV) events. A pooled analysis indicated a significantly lower risk of CV events or death in men with pre-existing CV disease (CVD) treated with degarelix vs GnRH agonists. We now report regional differences in baseline CV status and incidence of CV events in degarelix- and GnRH agonist-treated men. Methods: Individual patient level data on baseline CVD and subsequent CV events were pooled from 3 qualifying ( > 6 months exposure) phase 3 trials. CV events were analysed by geographic region: USA/Canada vs Europe and compared using cumulative incidence functions with all-cause mortality as the competing risk and Cox regression analyses. Results: Of 1737 men treated with degarelix and GnRH agonists, 404 (36.1%) and 215 (34.7%) had baseline CVD, respectively. By region, baseline CVD prevalence was similar between Europe (37.4%) and USA/Canada (33.5%; p = 0.085). However, CVD history was more severe in USA/Canada, (e.g. more myocardial infarction and coronary intervention). The presence of multiple CV risk factors were more frequent at baseline in the USA/Canada vs Europe (e.g. smoking [61.1% vs 39.0%], treated type 2 diabetes [17.9% vs 7.0%] and obesity [34.2% vs 16.7%], respectively) (p < 0.05). In men with baseline CVD, the cumulative incidence of a CV event was higher in USA/Canada (9.4, 95% CI 5.7–14.0) than Europe (3.5; 95% CI 1.9–5.7), p = 0.006 (Gray’s test). The treatment hazard ratio (HR; GnRH agonist as reference) was similar in the two regions (group-by-region interaction p = 0.979) with a homogenous HR of 0.42 (95% CI 0.20–0.87). Conclusions: Despite a similar proportion of patients with pre-existing CVD by region, baseline CV risk factors were more common and prior CVD more severe in USA/Canada vs Europe. Therefore geographical differences in the 1-year CV event risk (greater in USA/Canada) are likely due to patient clinical characteristics. Similar reduction in the risk of CV events compared to agonist was seen in degarelix patients in Europe and USA/Canada in line with the earlier reported overall rate.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.020 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".