Health-related quality of life (HRQOL) in patients (pts) with advanced gastric cancer/gastroesophageal junction cancer (GC/GEJC) or esophageal adenocarcinoma (EAC): Interim results of nivolumab plus chemotherapy (N+C) versus (C) from CheckMate 649.
Bibliographic record
Abstract
4066 Background: CheckMate 649 (NCT02872116) is a randomized, open label phase 3 study in first line (1L) GC/GEJC/EAC. Prespecified interim results showed statistically significant improvement in overall survival (OS) and progression-free survival (PFS) for N+C vs C in all randomized pts and pts whose tumors expressed programmed death-ligand 1 combined positive score (CPS) ≥ 5. We present interim HRQOL results for CPS ≥ 5 pts, included as exploratory in the study. Methods: HRQOL was assessed using EQ-5D-3L (EQ-5D) and Functional Assessment of Cancer Therapy–Gastric Cancer (FACT-Ga). Assessments were performed at baseline (BL), every 6 weeks during treatment, and during follow-up. Change from BL EQ-5D Visual Analog Scale (VAS), Utility Index (UI) and FACT-Ga scores were analyzed using mixed models. Time to first symptom deterioration (TTSD), time until definitive deterioration (TuDD), and time to improvement (TTI) were estimated with Kaplan-Meier estimators and stratified Cox models; deterioration/improvement was based on prespecified meaningful change thresholds. Results: 1,581 pts were randomized to N+C (n = 789) and C (n = 792); of those, 955 pts had CPS ≥ 5 (N+C [n = 473] and C [n = 482]). Among 821 pts with BL and post BL PROs (N+C [n = 421] and C [n = 400]), BL scores for FACT-Ga total were similar for N+C and C. Least-squares mean differences from BL favored N+C at most visits for EQ-5D and FACT-Ga total and GaCS, and were comparable for other FACT subscales (data not shown). TTI largely favored N+C (most hazard ratios (HR) > 1) but was not significantly different between treatments. For TTSD, pts treated with N+C had decreased risk of deterioration (HR < 1) in EQ-5D UI, FACT-Ga total, and GaCS. TuDD showed statistically significant delays in deterioration (HR with confidence intervals [CI] < 1) for all scores. Conclusions: Pts with 1L GC/GEJC/EAC experienced better HRQOL with N+C compared with C alone. Change from BL in EQ-5D and FACT-Ga total and GaCS favored N+C at most visits. N+C decreased deterioration risk compared to C with OS and PFS improvement, suggesting favorable benefits in 1L GC/GEJC/EAC pts with CPS ≥ 5. Clinical trial information: NCT02872116. [Table: see text]
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".