Safety and Efficacy of Sorafenib in Elderly Patients Treated in the North American Advanced Renal Cell Carcinoma Sorafenib Expanded Access Program
Bibliographic record
Abstract
OBJECTIVE: In this retrospective analysis of the Advanced Renal Cell Carcinoma Sorafenib (ARCCS) program in North America, we compared the safety and efficacy of sorafenib in patients aged ≥70 with those aged <70 years. METHODS: Patients were treated with oral sorafenib twice daily until the occurrence of disease progression or treatment intolerance. The primary objective of the ARCCS program was making sorafenib available to patients with advanced renal cell carcinoma (RCC) in the USA and Canada before marketing approval was obtained; the secondary objective was the evaluation of its safety and efficacy. RESULTS: Of the 2,504 patients enrolled in the ARCCS program who received at least 1 dose of sorafenib, 736 (29%) were aged ≥70 years. The most common grade ≥3 adverse events included rash/desquamation (5% in both groups), hand-foot skin reaction (8% in those aged ≥70 years vs. 10% in those <70 years of age), hypertension (5 vs. 4%) and fatigue (7 vs. 4%). Partial response was seen in 4% of the patients in both age groups. The median overall survival for the ≥70-year versus <70-year groups was also similar (46 vs. 50 weeks). CONCLUSIONS: There were no substantial differences in safety and efficacy between patients aged ≥70 and <70 years with advanced RCC treated with sorafenib.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".