Impact of concomitant cardiovascular therapies on efficacy and safety of relugolix verus leuprolide in men with advanced prostate cancer: Subgroup analysis from the phase 3 HERO study.
Bibliographic record
Abstract
101 Background: Cardiovascular (CV) events are the leading cause of death in prostate cancer. Men with prostate cancer are likely to have CV risk factors and CV-related concomitant medications. In the phase 3 HERO study, a 54% lower incidence of major adverse cardiac events was reported in men treated with the oral GnRH receptor antagonist relugolix vs leuprolide. Herein, we characterize the impact of concomitant CV therapies on efficacy and safety in the HERO study. Methods: In HERO, 930 men with advanced prostate cancer were randomized 2:1 and treated with relugolix (120 mg orally once daily [after single 360 mg loading dose] or leuprolide (injections every 3 months) for 48 weeks. Subgroups analyzed included men who received antihypertensives, antithrombotics, or lipid-modifying therapies, as well as the most common drug classes (>10%) and single most common agent within each class. Assessments included sustained testosterone suppression to castrate levels (<50 ng/dL) through 48 weeks and safety parameters (adverse events). Results: Antihypertensives, antithrombotics, and lipid modifying agents were utilized by 52.7%, 39.1%, and 39.6% of men in the HERO trial, respectively (table). In the main subgroups, point estimates for sustained castration rates were consistent with the overall estimates of relugolix and leuprolide observed in the overall population (table). Sustained castration rates were also consistent for men taking the most common drug classes (table) and individual agents in each class (losartan [n=103]: relugolix, 95.4% vs. leuprolide, 80.6%; amlodipine [n=229]: 97.2% vs. 85.5%; metoprolol [n=88]: 95.7% vs. 86.9%; acetylsalicylic acid [n=259]: 97.0% vs. 92.1%; clopidogrel [n=43]: 96.4% vs. 86.7%; simvastatin [n=78]: 98.0% vs. 87.3%). Incidence and types of adverse events were similar among men who received antihypertensives, antithrombotics, and lipid modifying agents during the trial. Conclusions: In the HERO trial, relugolix suppressed testosterone and was generally well tolerated when given with concomitant CV agents, with results consistent with those of the overall population. Clinical trial information: NCT03085095. [Table: see text]
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".