Sunitinib dose escalation after disease progression in metastatic renal cell carcinoma.
Bibliographic record
Abstract
458 Background: Previous pharmacologic studies demonstrated that higher sunitinib ( S) exposure is associated with improved clinical outcomes in metastatic renal cell carcinoma (mRCC) patients. We aimed to assess the efficacy and toxicity of S dose escalation in mRCC patients progressing on the standard 50mg dose. Methods: A single institution retrospective review was conducted on mRCC patients, treated outside trials with a 50 mg S dose given on an individualized schedule between October 2009 and January 2016, who subsequently progressed on imaging. At progression, patients were dose escalated to 62.5 and 75mg on an individualized schedule if toxicity permitted. Median Progression and Overall Survival (PFS, OS) were analyzed using the Kaplan Meier method. PFS1 and 2 were defined as the time between the start of sunitinib and first progression and the time between dose escalation and second progression respectively. Results: Twenty-five eligible patients were identified, with a median follow-up of 40.3 months (11.1-66.6) and a mean age of 54 years (12.4). The majority of patients underwent cytoreductive surgery (92%) and were men (88%). Thirty two percent, 44%, and 24% had a good, intermediate, and poor prognostic Heng score respectively. At the 50 mg doses, 60% and 16% of patients had a partial response (PR) and stable disease (SD) respectively with a median time to progression (TTP) of 11.4 months (95% CI, 3-20.7). After progression, 36% and 28% had PR and SD on higher doses of S respectively with a TTP of 7.8 months (95% CI, 6.3-12.4). Three patients with progressive disease as best response on a 50 mg S dose achieved SD (2/3) or PR (1/3) after dose escalation. The median PFS1, PFS2, and OS were 6.1 months (95% CI, 2.3-19.4), 6.7 months (95% CI, 3.1-8.4), and 63.7 months (95% CI, 26-not reached) respectively. The most common adverse events after dose escalation were fatigue (56%), diarrhea (40%), and skin toxicity (28%). Conclusions: Patients with mRCC who progress on a 50 mg S dose, may derive a clinical benefit and prolonged survival from dose escalation with acceptable toxicity profiles. These results need to be confirmed in well-designed prospective studies with the aim to optimize the duration of benefit from S therapy.
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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) | 0.001 | 0.001 |
| 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".