Pembrolizumab alone or with chemotherapy for recurrent/metastatic head and neck squamous cell carcinoma in KEYNOTE-048: subgroup analysis by Programmed Death Ligand-1 combined positive score
Bibliographic record
Abstract
Purpose: The phase III KEYNOTE-048 (ClinicalTrials.gov identifier: NCT02358031) trial of pembrolizumab in recurrent or metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) included planned efficacy analyses in the total population and in participants with programmed death ligand-1 (PD-L1) combined positive score (CPS) ≥ 1 and CPS ≥ 20. To further characterize the predictive value of PD-L1 expression on outcome, we conducted efficacy analyses in the PD-L1 CPS < 1 and CPS 1-19 subgroups in KEYNOTE-048. Methods: Participants with R/M HNSCC and no prior systemic therapy for R/M disease were randomly assigned 1:1:1 to pembrolizumab, pembrolizumab-chemotherapy, or cetuximab-chemotherapy. Post hoc efficacy analyses of the PD-L1 CPS < 1 and CPS 1-19 subgroups were performed. Results: Of 882 participants enrolled, 128 had PD-L1 CPS < 1 and 373 had CPS 1-19. For pembrolizumab versus cetuximab-chemotherapy, the median overall survival was 7.9 versus 11.3 months in the PD-L1 CPS < 1 subgroup (hazard ratio [HR], 1.51 [95% CI, 0.96 to 2.37]) and 10.8 versus 10.1 months in the CPS 1-19 subgroup (HR, 0.86 [95% CI, 0.66 to 1.12]). For pembrolizumab-chemotherapy versus cetuximab-chemotherapy, the median overall survival was 11.3 versus 10.7 months in the PD-L1 CPS < 1 subgroup (HR, 1.21 [95% CI, 0.76 to 1.94]) and 12.7 versus 9.9 months in the CPS 1-19 subgroup (HR, 0.71 [95% CI, 0.54 to 0.94]). Conclusion: Increased efficacy of pembrolizumab or pembrolizumab-chemotherapy was observed with increasing PD-L1 expression. PD-L1 CPS < 1 subgroup analysis was limited by small participant numbers. Results from the PD-L1 CPS 1-19 subgroup support previous findings of treatment benefit with pembrolizumab monotherapy and pembrolizumab-chemotherapy in patients with PD-L1 CPS ≥ 1 tumors. Although PD-L1 expression is informative, exploration of additional predictive biomarkers is needed for low PD-L1-expressing 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| 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) | 0.003 | 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".