Learning Experiences with Sunitinib Continuous Daily Dosing in Patients with Pancreatic Neuroendocrine Tumours
Bibliographic record
Abstract
Molecular strategies to improve outcomes for patients with pancreatic neuroendocrine tumours (nets) have focused on targeting vascular endothelial growth factor, platelet-derived growth factor, and mtor (the mammalian target of rapamycin). This approach has led to the regulatory approval of two molecularly targeted agents for advanced pancreatic nets: sunitinib, a multi-targeted tyrosine kinase inhibitor, and everolimus, an mtor inhibitor. Initial experience with sunitinib in advanced pancreatic net was gained from the phase iii registration trial, which used a continuous daily dosing (cdd) schedule instead of daily drug administration for 4 consecutive weeks every 6 weeks (schedule 4/2), the approved schedule for advanced renal cell carcinoma (rcc) and gastrointestinal stromal tumour (gist). Clinical experience gained with schedule 4/2 in rcc and gist shows that, using a therapy management approach, patients can start and be maintained on the recommended dose and schedule, thus optimizing treatment outcomes. Here, we discuss challenges that can potentially be faced by physicians who use sunitinib on the cdd schedule, and we use clinical data and real-life clinical experience to present therapy management approaches that support cdd in advanced pancreatic net.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".