The efficacy and safety of sunitinib given on an individualised schedule as first-line therapy for metastatic renal cell carcinoma: A phase 2 clinical trial
Bibliographic record
Abstract
BACKGROUND: Sunitinib is administered on a rigid schedule that may not be optimal for all patients. We hypothesised that toxicity-driven dose and schedule changes would optimise drug exposure and outcome for each patient. MATERIALS AND METHODS: In a phase 2 trial, 117 patients with metastatic clear cell renal cell cancer were started on sunitinib 50 mg/day with the aim to treat for 28 days. Treatment breaks were reduced to 7 days. Sunitinib dose and the number of days on therapy were individualised based on toxicity aiming for ≤ grade II toxicity with dose escalation in patients with minimal toxicity. The null hypothesis for the primary end-point was a progression-free survival (PFS) of 8.5 months based on a study with similar eligibility criteria. RESULTS: The null hypothesis was rejected (p < 0.001) with a median PFS of 12.5 months (95% confidence interval [CI]: 9.6-16.5). The median overall survival was 38.5 months (95% CI: 28.3-not reached). The objective response rate (46.1%) and stable disease rate (38.5%) translated into a clinical benefit for 84.6% of patients with no decline in quality of life scores during therapy. Fewer patients were dose reduced (26.5% vs. 50%) or discontinued due to toxicity (7.7 vs. 18-20%) compared to standard sunitinib dosing, and 20 (18.4%) patients were dose escalated to 62.5 mg (12) and 75 mg (8) with a wide individual variation in the optimal dose and treatment duration. CONCLUSIONS: Individualised sunitinib therapy is feasible, safe and an effective method to manage toxicity with one of the best efficacy seen for oral vascular endothelial growth factor inhibitors in metastatic renal cell carcinoma. CLINICALTRIALS. GOV IDENTIFIER: NCT01499121.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".