Vascular endothelial growth factor (VEGF) therapy in metastatic renal cell carcinoma (mRCC): Differences between Asian and non-Asian patients.
Bibliographic record
Abstract
451 Background: Several reports have indicated that VEGF targeted therapy in metastatic renal cell carcinoma (mRCC) may be more toxic in the Asian versus Caucasian populations. Comparative efficacy of these agents with respect to ethnicity is not well characterized. Methods: Eight centers participating in the International mRCC Database Consortium with available dose reduction data on patients with mRCC treated with VEGF targeted therapy were included in this analysis. Asian patients were derived from centers in Korea and Singapore. Results: 1024 patients with a median follow-up of 29.4 months were included in this analysis. Baseline characteristics are below. The percentage of dose modifications/reductions between non-Asians and Asians was similar (55% vs 61% p=0.1197) but more patients completely discontinued treatment due to toxicity in the non-Asian vs the Asian group (28% vs 21% p=0.0197). When adjusted for the Heng et al poor prognostic criteria, there was no difference in overall survival (HR 0.887, 95%CI 0.729-1.08, p=0.2322) or progression-free survival (HR 1.069, 95%CI 0.910-1.256, p=0.4184) between non-Asians and Asians. Interestingly, when patients were dose reduced due to toxicity, they had a longer treatment duration and overall survival than those that did not require a dose reduction in both the non-Asian (10.6 vs 5.0 months p<0.0001 and 22.6 vs 16.1 months p=0.0016, respectively) and in the Asian populations (8.9 vs 5.4 months p=0.0028 and 28.0 vs 18.7 months p=0.0069). Conclusions: After adjusting for risk groups, there appears to be no difference in outcome between Asians vs. non-Asian patients with mRCC treated withVEGF-targeted therapy. Judicious dose reductions may allow for better outcomes in both populations possibly due to longer treatment durations, but direct comparisons are needed. [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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".