Multicenter phase II trial of temsirolimus (TEM) and bevacizumab (BEV) in pancreatic neuroendocrine tumor (PNET): Results of a planned interim efficacy analysis.
Bibliographic record
Abstract
4047 Background: PNET has long had few effective therapies other than chemotherapy. Recent placebo-controlled phase III trials of the mTOR inhibitor everolimus and the VEGF/ PDGF receptor inhibitor sunitinib noted improved progression-free survival (PFS). However, objective response rates (RR) with these agents are still <10%. Preclinical studies suggest enhanced anti-tumor effects with combined mTOR and VEGF targeted therapy. Methods: We conducted a phase II trial of the mTOR inhibitor TEM (25 mg IV q week) and the VEGF-A monoclonal antibody BEV (10 mg/kg IV q 2 weeks) in patients (pts) with well or moderately differentiated PNET and progressive disease by RECIST within 7 months of study entry. Co-primary endpoints were RR and 6-month PFS. Planned enrollment is 50 patients, with interim analysis for futility after the first 25 evaluable pts. Pts had no prior mTOR or VEGF targeted agents, ECOG PS 0-1, and adequate hematologic and organ function. Continued octreotide was allowed, but not required. Prior interferon, embolization, and ≤ 2 chemotherapy regimens were allowed. Results: Confirmed PR was documented in 13 of the first 25 (52%) evaluable patients. 21 of 25 (84%) patients were progression-free at 6 months. Both endpoints exceeded the protocol-defined criteria to continue enrollment. For 36 evaluable patients, the most common grade 3-4 adverse events attributed to therapy were hypertension (14%), leukopenia (11%), lymphopenia (11%), hyperglycemia (11%), mucositis (8%), hypokalemia (8%), and fatigue (8%). Conclusions: The combination of TEM/BEV has substantial activity in a multi-center phase II trial with RR of 52%, well in excess of single targeted agents in PNET. 6-month PFS was a notable 84% in a population of patients with RECIST criteria progression within 7 months of study entry. Accrual is ongoing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".