A phase I study of nivolumab (anti-PD-1; BMS-936558; ONO-4538) in combination with sunitinib, pazopanib, or ipilimumab in patients (pts) with metastatic renal cell carcinoma (mRCC).
Bibliographic record
Abstract
TPS4593 Background: Vascular endothelial growth factor receptor-tyrosine kinase inhibitors are established therapies for mRCC. However, sunitinib and pazopanib rarely elicit durable responses. Programmed death-1 receptor (PD-1) is an immune checkpoint modulator that suppresses T-cell activation by interacting with its ligands (PD-L1/2) on antigen presenting cells and some tumor cells. Nivolumab, a PD-1 receptor blocking antibody, has shown durable responses in previously treated pts with mRCC in Phase 1 and 2 trials. Ipilimumab is an immune checkpoint inhibitor (anti-CTLA-4 antibody) already approved for the treatment of advanced melanoma. We describe an ongoing Phase 1 dose-escalation and expansion study evaluating combination of nivolumab with sunitinib, pazopanib or ipilimumab in pts with mRCC. Methods: Patients with histologically confirmed mRCC are treated on 4 parallel arms: nivolumab 2.0 or 5.0 mg/kg + sunitinib standard dosing (Arm S), nivolumab 2.0 or 5.0 mg/kg + pazopanib standard dosing (Arm P), nivolumab 3 mg/kg + ipilimumab 1 mg/kg as induction (Arm I-1), and nivolumab 1 mg/kg + ipilimumab 3 mg/kg as induction (Arm I-3) with nivolumab 3 mg/kg maintenance for both arms. Arms S and P are being conducted in 2 phases: nivolumab dose-escalation phase for previously treated pts (≤18 pts/arm) and then dose-expansion phase for treatment-naïve pts (20 pts/arm) if the maximum tolerated dose is ≥5 mg/kg. Arms I-1 and I-3 are fixed-dose cohorts (20 pts/arm) including both treatment-naïve and previously treated pts. Most of the study population consists of pts with clear-cell histology; non-clear cell mRCC pts are allowed in the dose-escalation cohorts of Arms S and P. The primary objectives are to assess safety and tolerability, and to determine the recommended Phase 2 dose in pts with mRCC. The secondary objective is to assess preliminary antitumor activity (objective response rate and response duration per RECIST 1.1). Exploratory objectives are to evaluate overall survival, pharmacodynamics, and predictive biomarkers for the combinations, and pharmacokinetics and immunogenicity of nivolumab. Clinical trial information: NCT01472081.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".