Ziv-aflibercept plus pembrolizumab in patients with advanced melanoma resistant to anti-PD-1 treatment
Bibliographic record
Abstract
BACKGROUND: Vascular endothelial growth factor is associated with reduced immune response and impaired anti-tumor activity. Combining antiangiogenic agents with immune checkpoint inhibition can overcome this immune suppression and enhance treatment efficacy. METHODS: This study investigated the combination of ziv-aflibercept anti-angiogenic therapy with pembrolizumab in patients with advanced melanoma resistant to anti-PD-1 treatment. Baseline and on-treatment plasma and PBMC samples were analyzed by multiplex protein assay and mass cytometry, respectively. RESULTS: In this Phase 1B study (NCT02298959), ten patients with advanced PD-1-resistant melanoma were treated with a combination of ziv-aflibercept (at 2-4 mg/kg) plus pembrolizumab (at 2 mg/kg), administered intravenously every 2 weeks. Two patients (20%) achieved a partial response, and two patients (20%) experienced stable disease (SD) as the best response. The two responders had mucosal melanoma, while both patients with SD had ocular melanoma. The combination therapy demonstrated clinical activity and acceptable safety, despite the occurrence of adverse events. Changes in plasma analytes such as platelet-derived growth factor and PD-L1 were explored, indicating potential alterations in myeloid cell function. Higher levels of circulating CXCL10 in non-responding patients may reflect pro-tumor activity. Specific subsets of γδ T cells were associated with poor clinical outcomes, suggesting impaired γδ T-cell function in non-responding patients. CONCLUSIONS: Although limited by sample size and follow-up, these findings highlight the potential of the combination of ziv-aflibercept antiangiogenic therapy with pembrolizumab in patients with advanced melanoma resistant to anti-PD-1 treatment and the need for further research to improve outcomes in anti-PD-1-resistant melanoma. TRIAL REGISTRATION NUMBER: NCT02298959.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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 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".