Effect of an individualized dose/schedule strategy for sunitinib in metastatic renal cell cancer (mRCC) on progression-free survival (PFS): Correlation with dynamic microbubble ultrasound (DCE-US) data.
Bibliographic record
Abstract
356 Background: Sunitinib area under the curve (AUC) correlates with response and PFS (Houk et al). Current recommendations for dose modification do not take this into account. Methods: A single center retrospective review identified mRCC patients (pts) where individualized (individ) sunitinib dose/schedule modifications (DSM) were used to maximize dose and minimize time off therapy (Rx). Pts were started on 50 mg 28 days (d) on/14 d off. DSM were done to keep toxicity (fatigue, skin, GI) at ≤ grade-2. DSM-1 was 50 mg 14 d/7 d with individ increases in d on Rx based on toxicity. DSM-2 was 50 mg 7 d/7 d with individ increases in d on Rx. DSM-3 was 37.5 mg continuously with individ 7 d breaks. DSM-4 was 25 mg continuously with individ 7 d breaks. Results: In 171 pts; median age was 60y; 20% good, 60% intermediate, 20% poor prognosis by Heng criteria; 80% had nephrectomy; 79% clear cell histology; 60% were previously untreated. At a median follow-up of 10.7 months (mo), overall median PFS was 7.9 mo. Of 39 pts still on therapy, 37 were on a DSM Rx. Pts were allocated to three groups based on the dose/schedule used for the longest time. The PFS/response% (PR+SD) for each group was 4.4 mo/65.6% (standard 50 mg 28 d/14 d; 43 pts), 8.0 mo/78.2% (DSM-1/DSM-2; 69 pts) and 10.4 mo/81.3% (DSM-3/DSM-4; 59 pts) with improved PFS (p=0.001) in both DSM groups vs. the standard schedule but no difference in response. 30 pts were studied by DCE-US at baseline, and after 7 d and 14 d on Rx or after 14 d and 28 d on Rx. In responding pts, tumor blood volume decreased at d 7 and again at d 14 vs. baseline but was stable or increased at d 28 vs. d 14. A rebound was seen after 14 d off Rx. Conclusions: Based on the U.S. data, previous pharmacokinetic data (steady state at 10-14 d) and this clinical data, starting pts on 50 mg 14 d/7 d followed by individ DSM may be safe and active. This DSM strategy, was associated with a favorable toxicity profile, apparent improvement in PFS and a good PR+SD rate in a group of unselected mRCC pts, warranting confirmation in a prospective trial. Pts that tolerate 50 mg 28 d/14 d with minimum toxicity may need dose escalation and/or less time off therapy to optimize PFS. [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 | 0.003 |
| 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) | 0.000 | 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 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".