Sunitinib rechallenge in metastatic renal cell carcinoma patients
Bibliographic record
Abstract
BACKGROUND: Sunitinib was a standard initial therapy in metastatic renal cell carcinoma (mRCC). Given the fact that many patients progressed through many available therapies and antitumor activity had been demonstrated with sequential vascular endothelial growth factor-targeting approaches, a retrospective review was performed of the experience of rechallenge with sunitinib in sunitinib-refractory mRCC. METHODS: mRCC patients who received sunitinib therapy after disease progression on prior sunitinib and other therapy were retrospectively identified. Patient characteristics, toxicity, clinical outcome, Response Evaluation Criteria in Solid Tumors (RECIST) objective response rate, and progression-free survival (PFS) were recorded. RESULTS: Twenty-three mRCC patients who were rechallenged with sunitinib were identified. Upon rechallenge, 5 patients (22%) achieved an objective partial response. The median PFS with initial treatment was 13.7 months and 7.2 months with rechallenge. Patients with >6-month interval between sunitinib treatments had a longer PFS with rechallenge than patients who started the rechallenge within 6 months (median PFS, 16.5 vs 6.0 months; P=.03). There was no significant difference in outcome to sunitinib rechallenge based on number or mechanism of intervening treatments. Substantial new toxicity or significantly increased severity of prior toxicity was not seen during rechallenge in this cohort. CONCLUSIONS: Sunitinib rechallenge had potential benefits and was tolerated in select metastatic RCC patients. Additional prospective investigation was warranted.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".