Health-related quality of life (HRQoL) outcomes from the randomized, double-blind phase 3 KEYNOTE-671 study of perioperative pembrolizumab for early-stage non-small-cell lung cancer (NSCLC).
Bibliographic record
Abstract
8012 Background: Neoadjuvant pembrolizumab + cisplatin-based chemotherapy (neoadj pembro + chemo), resection, and adjuvant (adj) pembro (pembro arm; n=397) significantly improved EFS, OS, pCR, and mPR and had an expected safety profile versus neoadj placebo (pbo) + chemo, resection, and adj pbo (pbo arm; n=400) in patients (pts) with resectable stage II, IIIA, or IIIB (N2) NSCLC. We present prespecified pt-reported outcome (PRO) endpoints from KEYNOTE-671. Methods: Pts completed EORTC QLQ-C30 and QLQ-LC13 questionnaires at baseline (BL), the last scheduled presurgery visit, adj cycles 1-4, 7, 10, and 13, and each post treatment visit. A constrained longitudinal data analysis model was used to estimate least squares mean (LSM) score changes from BL to neoadj wk 11 and adj wk 10 (latest time of ≥60% completion and ≥80% compliance) in QLQ-C30 global health status (GHS)/QoL, physical functioning (PF), role functioning (RF), and dyspnea and QLC-LC13 cough and chest pain in all treated pts who completed ≥1 PRO assessment. Data are from interim analysis 2 (10 Jul 2023 cutoff). Results: Across arms, questionnaire completion was ≥87% at neoadj wk 11 and ≥62% at adj wk 10; compliance was ≥87% and ≥92%, respectively. There were no differences in LSM change from BL in the neoadj or adj phase for any PRO score (Table). Conclusions: Adding perioperative pembro maintained HRQoL in both the neoadj and adj settings versus neoadj chemo and surgery alone in pts with resectable early-stage NSCLC. Together with the significant efficacy improvements and absence of new safety signals, HRQoL data support the perioperative pembro regimen as a new standard of care. Clinical trial information: NCT03425643 . [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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 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 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".