Abstract 18632: Variation in Patient Profiles and Outcomes in US and non-US Subgroups of the Cangrelor versus Standard Therapy to Achieve Optimal Management of Platelet Inhibition (CHAMPION) PHOENIX Trial
Bibliographic record
Abstract
Objectives: To describe the clinical profiles, safety and efficacy endpoints, and response to cangrelor in US and non-US subgroups. Background: CHAMPION PHOENIX demonstrated superiority of cangrelor in reducing ischemic events at 48 hours in patients undergoing percutaneous coronary intervention (PCI) compared with clopidogrel. Methods: We analyzed all patients included in the modified intention-to-treat analysis in US (n=4,097; 37.4%) and non-US subgroups (n=6,845; 62.6%). Results: The US cohort was older and had higher rates of cardiovascular risk factors and prior cardiovascular procedures. US patients more frequently underwent PCI for stable angina (72.4% vs. 46.4%). Utilization of clopidogrel loading doses of 600mg and bivalirudin was also higher in US vs. non-US participants. At 48 hours, rates of the primary composite endpoint were lower in the cangrelor arm compared with the clopidogrel arm in US (4.5% vs. 6.4%; OR 0.71 [0.54-0.92]) and in non-US patients (4.8% vs. 5.6%; OR 0.85 [0.69-1.05]); interaction P=0.26 ( Table ). Similarly, rates of the key secondary endpoint, stent thrombosis, were reduced by cangrelor in both regions. Rates of GUSTO (Global Use of Strategies to Open Occluded Arteries)-defined severe bleeding were low and not significantly increased by cangrelor in either region. Conclusions: Despite broad differences in clinical profiles and indications for PCI by region in a large global cardiovascular clinical trial, cangrelor consistently reduced rates of ischemic endpoints compared with clopidogrel without an excess in severe bleeding in both US and non-US subgroups.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.004 | 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".