Abstract CT561: KeyVibe-003: Randomized, double-blind, phase 3 study of first-line pembrolizumab with and without vibostolimab (anti-TIGIT) in patients with PD-L1-positive metastatic NSCLC
Bibliographic record
Abstract
Abstract Background: Vibostolimab (MK-7684) is a humanized monoclonal antibody (mAb) that binds to the T-cell immunoreceptor with immunoglobulin and ITIM domains (TIGIT), blocking the interaction between TIGIT and its ligands, CD112 and CD155. Pembrolizumab, an anti-PD-1 mAb, significantly improves OS versus chemotherapy in patients with PD-L1-positive advanced non-small-cell lung cancer (NSCLC). In the first-in-human study (NCT02964013), the combination of vibostolimab plus pembrolizumab had a manageable safety profile and showed promising antitumor activity in patients with advanced NSCLC naive to anti-PD-(L)1 therapy; ORR was 31% and 25% in patients with PD-L1 tumor proportion score (TPS) ≥1% and less than 1%, respectively. The current phase 3 study (KeyVibe-003; ClinicalTrials.gov, NCT04738487) is comparing first-line treatment with MK-7684A, a co-formulation of vibostolimab plus pembrolizumab, versus pembrolizumab monotherapy in patients with PD-L1-positive metastatic NSCLC. Methods: This randomized, multicenter, double-blind study is enrolling adults with pathologically confirmed, previously untreated, metastatic NSCLC with PD-L1 TPS ≥1% (centrally confirmed). Patients must have measurable disease per RECIST v1.1, an ECOG PS of 0-1, have no EGFR mutations or ALK or ROS1 gene rearrangements, and have no active or untreated CNS metastases. Patients are randomized 1:1 to receive intravenous treatment with vibostolimab 200 mg plus pembrolizumab 200 mg Q3W or pembrolizumab 200 mg Q3W for up to 35 cycles (approximately 2 years) or until PD, unacceptable AEs, intercurrent illness, or investigator decision. Patients who stop treatment after a CR or after completing 35 cycles and subsequently have PD can receive up to 17 additional cycles (approximately 1 year) of their randomized therapy. Randomization is stratified by ECOG PS (0 vs 1), PD-L1 TPS (1%-49% vs ≥50%), and region of enrollment (East Asia vs non-East Asia). The dual primary endpoints are PFS, per RECIST v1.1 by blinded independent central review (BICR), and OS. Secondary endpoints include ORR and DOR per RECIST v1.1 by BICR, patient-reported outcomes, and safety. Radiographic imaging occurs at baseline, Q9W from randomization through week 54, and then Q12W until PD, the start of new anticancer treatment, withdrawal of consent, or death. Health-related quality of life is assessed using validated patient-reported outcome instruments including the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30. AEs are graded according to National Cancer Institute Common Terminology Criteria for Adverse Events v5.0. Enrollment began in April of 2021, and is ongoing at 83 sites in 15 countries. Results: N/A Conclusions: N/A Citation Format: Byoung Chul Cho, Rosalyn A. Juergens, Ying Cheng, Gilberto de Castro Jr., Mustafa Erman, Jessica R. Bauman, Toshiaki Takahashi, Paul Schwarzenberger, Chengxiang Li, M. Catherine Pietanza, James Chih-Hsin Yang. KeyVibe-003: Randomized, double-blind, phase 3 study of first-line pembrolizumab with and without vibostolimab (anti-TIGIT) in patients with PD-L1-positive metastatic NSCLC [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr CT561.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".