Health-related quality of life outcomes from KEYNOTE-412: chemoradiotherapy with or without pembrolizumab in participants with head and neck squamous cell carcinoma
Bibliographic record
Abstract
Background: The health-related quality of life (HRQoL) of patients with locally advanced head and neck squamous cell carcinoma (LA HNSCC) is impacted by both disease- and treatment-related factors. Treatments that preserve and maximize HRQoL in this setting represent a substantial unmet need. Methods: KEYNOTE-412 (NCT03040999) was a randomized, double-blind, placebo-controlled phase 3 study of pembrolizumab plus chemoradiotherapy (CRT) versus placebo plus CRT for maintenance therapy in participants with treatment-naïve LA HNSCC. Patient-reported outcomes (PROs) assessed using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) and EORTC QLQ Head and Neck 35 (H&N35) were pre-specified secondary endpoints and administered at baseline and throughout the study. Least squares mean (LSM) change from baseline was assessed using a constrained longitudinal data analysis model. No formal statistical significance testing was performed. Results: The PRO analysis population included 395 participants randomized to receive pembrolizumab plus CRT and 397 to receive placebo plus CRT. Completion rates for all assessed PROs were >95% at baseline and >66% at week 45. LSM change from baseline to week 45 was similar between groups across EORTC QLQ-C30 and QLQ-H&N35 subscale scores. There were no notable differences in empirical mean change or the proportion of participants with improvement, stability, or deterioration from baseline to week 45 between treatment groups. Conclusion: The addition of pembrolizumab to CRT did not meaningfully impact HRQoL in participants with LA HNSCC.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".