Comparision of the risk of cardiovascular events and death in patients treated with degarelix compared with LHRH agonists.
Bibliographic record
Abstract
42 Background: LHRH agonists are used to treat patients (pts) with advanced prostate cancer and have been associated with an increased risk of cardiovascular (CV) events and related deaths. Degarelix is a GnRH antagonist that appears to mitigate this risk. Methods: Results were pooled from 2328 pts participating in 6 prospective randomised trials. Most pts (n=1,686) received 1 year of GnRH antagonist or LHRH agonist treatment; the remainder (n=642) had 3–7 months’ treatment. Data were classified based on the MedDRA system and analysed using Kaplan Meier plots and a Cox proportional hazard model. Event analysis was based on death from any cause or CV event defined as arterial embolic/thrombotic; haemorrhagic or ischemic cerebrovascular; myocardial infarction or other ischemic heart disease. High risk pts were defined as men with a baseline CV disease (CVD) history. Results: Treatment groups (GnRH antagonist, n=1,491 [degarelix]; LHRH agonist, n=837 [goserelin, n=458; leuprolide, n=379]) were balanced for baseline characteristics and CVD history (31% vs. 29%). Characteristics associated with CVD (e.g. statin medication, elevated blood pressure, diabetes, cholesterol >6.2 mmol/L) were similar between groups. The risk of a CV event or death was significantly lower in pts receiving degarelix during the first year of treatment (see Table). In pts with baseline CVD the findings remained significant. In pts with no baseline CVD, there was no difference in subsequent CVD events or death in either group. In analysis by time to CV event only in all pts and pts with baseline CVD (see Table), men receiving GnRH antagonist had a significantly lower risk of CV events. Conclusions: In all pts treated with a GnRH antagonist (degarelix) risk of a CV event or death was significantly lower than in pts receiving an LHRH agonist over a treatment period of up to 1 year. In pts with baseline CVD, risk reduction remained significant at ~50%. [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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".