Cardiac safety analysis for a phase III trial of sunitinib (SU) or sorafenib (SO) or placebo (PLC) in patients (pts) with resected renal cell carcinoma (RCC).
Bibliographic record
Abstract
4500 Background: We performed a cardiac analysis of E2805, a well population of pts with resected high risk RCC. The objectives were to determine if pts treated with SU or SO had clinically significant decreases in left ventricular (LV) ejection fraction (EF) and to describe the frequency of clinically significant heart failure (HF). We also report the frequency of other events including (un)stable angina or myocardial infarction. Methods: EF was measured by multiple gated acquisition scan (MUGA) at baseline, 3, 6, and 12 months (mo), and end of treatment, if symptoms developed, and 3 mo after the last abnormal assessment. The primary cardiac endpoint was defined as an EF decline < the institutional lower limit of normal (ILN) that was a ≥ 16% decline from baseline, and that occurred ≤ 6 mo into therapy. Clinically significant HF was ≥ Grade 3 LV systolic or diastolic dysfunction (severe symptoms with any activity or from drop in EF responsive (Grade 3) or refractory (Grade 4) to therapy. Late LVEF events were a drop in LVEF of ≥ 16% occurring after 6 mo of therapy. Event rates on each treatment arm were calculated, with 90% exact binomial confidence intervals (CI). Results: Post-baseline MUGAs are available for 1589 of 1943 total pts accrued. 1293 pts had MUGA assessment ≥ 6 mo. 21 pts had primary events (Table). 71 pts had worst LVEF declines of ≥16% from baseline, including 52 of which occurred ≤ 6 mo from baseline, with the majority not meeting full primary event criteria. There were 11 reported grade 3 LV systolic events (5 SU, 4 SO and 2 PLC). 8 pts had cardiac ischemia possibly or probably from agent. Only one grade 4 event followed a primary LVEF event. 4 of 7 pts who began treatment with LVEF
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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 | 0.002 |
| 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 | 0.000 |
| 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".