A phase I study of BMS-936558 plus sunitinib or pazopanib in patients with metastatic renal cell carcinoma.
Bibliographic record
Abstract
TPS2614 Background: Standard treatments for metastatic renal cell carcinoma (mRCC) block the vascular endothelial growth factor pathway (eg, sunitinib, pazopanib) or mammalian target of rapamycin pathway (e.g., temsirolimus, everolimus). However, most patients (pts) develop resistance and complete responses are rare. Upregulation of programmed death-1 (PD-1) in tumor infiltrating lymphoctyes, and its ligand PD-L1 in tumors, is associated with more aggressive disease and poor prognosis. Blocking the PD-1/PD-L1 interaction is a novel immunotherapeutic approach for mRCC. In preliminary results of a phase I trial, the anti-PD-1 monoclonal antibody BMS-936558 had antitumor activity in pts with advanced tumors, including objective responses (ORs) in 6 of 18 pts with mRCC. Here we describe a phase I study planned to evaluate the safety, tolerability, and maximum tolerated dose (MTD) of BMS-936558, when combined with sunitinib or pazopanib in pts with mRCC. Methods: This open-label study will have two parallel treatment arms (BMS-936558 plus sunitinib and BMS-936558 plus pazopanib) conducted in two parts (dose escalation and dose expansion). Pts must have received ≥1 prior systemic therapy to be eligible for dose escalation. Only treatment-naïve pts will be eligible for dose expansion. Up to 36 pts (18 per arm) will be treated in the dose-escalation phase. After determining the MTD of BMS-936558, treatment-naïve pts will be enrolled to expansion cohorts allowing 24 pts to be treated at the MTD of each arm. Each treatment cycle will be 6 weeks, with BMS-936558 dosed on Days 1 and 22 and sunitinib or pazopanib given according to product label. Adverse events will be graded according to NCI CTCAE v4.0. Disease will be assessed every 6 weeks for the first four assessments and then every 12 weeks until disease progression. Pts will be treated until unacceptable toxicity, disease progression, or withdrawal of consent. The safety profile in pts treated at the MTD will be used to determine the recommended phase II study dose of BMS-936558 in each combination arm. Secondary objectives will include OR rate and duration of response based on RECIST 1.1. Exploratory analyses will investigate predictive biomarkers of BMS-936558.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".