Randomized Phase II Trial of Pazopanib Versus Placebo in Patients With Advanced Extrapancreatic Neuroendocrine Tumors (Alliance A021202)
Bibliographic record
Abstract
PURPOSE Patients with advanced, well-differentiated extrapancreatic neuroendocrine tumors (epNETs) have limited systemic treatment options. Pazopanib, an oral multikinase inhibitor with activity against vascular endothelial growth factor receptor (VEGFR)-2 and -3, PDGFR-alpha and-beta, and c-Kit, was tested for efficacy in epNET. PATIENTS AND METHODS We conducted a multicenter, randomized, double-blind, phase II study of pazopanib (800 mg once daily) versus placebo in low- to intermediate-grade epNET with radiologic progressive disease (PD) within 12 months of study entry. Previous somatostatin analog (SSA) was required for midgut tumors, and concurrent SSA was allowed. The primary end point was progression-free survival (PFS) by blinded independent central review. Unblinding and crossover were allowed if PD was confirmed by central review. RESULTS One hundred seventy-one patients (97 pazopanib and 74 placebo) were randomly assigned between September 2013 and October 2015. The majority had a midgut primary site (75%) and previous SSA treatment (93%). About half (49%) of the patients had functional tumors. The median follow-up was 61 months (95% CI, 60 to 63). Median PFS was 11.8 versus 7.6 months in pazopanib versus placebo, respectively (hazard ratio, 0.54 [95% CI, 0.37 to 0.79]; P < .001); 49 placebo patients crossed over to pazopanib. There was no significant difference in overall survival between the treatment arms. Rates of grade 3 or greater adverse events (regardless of attribution) were higher in pazopanib versus placebo (84% v 47%; P < .001), as were grade 5 death events (8% v 0%, P = .017). CONCLUSION Pazopanib compared with placebo significantly improves PFS in patients with progressive epNET, confirming that the VEGF signaling pathway is a valid target for therapy in epNET. However, after integrating the associated risks relative to the benefits, further development of pazopanib in this clinical context is not planned.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".