CheckMate 577: A randomized, double-blind, phase 3 study of adjuvant nivolumab (nivo) or placebo in pts with resected esophageal (E) or gastroesophageal junction (GEJ) cancer.
Bibliographic record
Abstract
TPS4131 Background: Expression of the PD-1 ligands PD-L1 and PD-L2 has been reported in ≈ 40% of pts with E/GEJ cancer and is associated with a poor prognosis. In a phase 3 trial, the PD-1 inhibitor nivo demonstrated an OS benefit vs placebo (HR, 0.63; P < 0.0001), resulting in a 37% reduction in the risk of death and double the OS rate at 12 mo (27% vs 11%) in pts with advanced gastric (G)/GEJ cancer refractory to ≥ 2 lines of chemotherapy (Kang YK, et al. J Clin Oncol. 2017;35 (suppl 4S) [abstract 2]). In this study, nivo was well tolerated, with a safety profile comparable with that of the placebo arm. These results indicate that nivo could be a new standard of care (SOC) for pts with heavily pretreated advanced G/GEJ cancer and provide a strong rationale to explore nivo in earlier lines of treatment for G/E/GEJ cancer. Currently, no effective adjuvant SOC is available after chemoradiotherapy (CRT) followed by resection for pts with E/GEJ cancer. This multinational, double-blind, phase 3 trial will evaluate nivo as an adjuvant therapy for pts with resected E/GEJ cancer (CheckMate 577; NCT02743494). Methods: In this study, an estimated 760 pts aged ≥ 18 years with stage II/III E/GEJ cancer are randomized to receive nivo or placebo. Prior to randomization, pts must have completed preoperative CRT followed by surgery and been diagnosed with residual pathologic disease after being surgically rendered free of disease with negative margins following complete resection. Pts with stage 4 resectable disease, cervical esophageal cancer, or those who have not received concurrent CRT prior to surgery are not eligible for study enrollment. Primary endpoints are OS and disease-free survival. Other key endpoints include the OS rate at 1, 2, and 3 years and safety. Clinical trial information: NCT02743494.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 |
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".