Pembrolizumab versus methotrexate, docetaxel, or cetuximab in recurrent or metastatic head and neck squamous cell carcinoma (KEYNOTE-040): Subgroup analysis by pattern of disease recurrence
Bibliographic record
Abstract
BACKGROUND: In the phase 3 KEYNOTE-040 study, pembrolizumab prolonged OS versus chemotherapy in previously treated recurrent or metastatic (R/M) HNSCC. We present a post hoc subgroup analysis by disease recurrence pattern: recurrent-only, recurrent and metastatic (recurrent-metastatic), and metastatic-only HNSCC. MATERIALS AND METHODS: Patients had HNSCC that progressed during or after platinum-containing treatment for R/M disease or had recurrence or progression within 3-6 months of previous platinum-containing definitive therapy for locally advanced disease. Patients were randomly assigned (1:1) to pembrolizumab 200 mg Q3W or investigator's choice of standards of care (SOC): methotrexate, docetaxel, or cetuximab. Outcomes included OS, PFS, ORR, and DOR. The data cutoff was May 15, 2017. RESULTS: There were 125 patients (pembrolizumab, 53; SOC, 72) in the recurrent-only subgroup, 204 in the recurrent-metastatic subgroup (pembrolizumab, 108; SOC, 96), and 166 in the metastatic-only subgroup (pembrolizumab, 86; SOC, 80). The hazard ratio (95% CI) for death for pembrolizumab versus SOC was 0.83 (0.55-1.25) in the recurrent-only, 0.78 (0.58-1.06) in the recurrent-metastatic, and 0.74 (0.52-1.05) in the metastatic-only subgroups. PFS was similar between treatment arms in all subgroups. ORR was 22.6% for pembrolizumab versus 16.7% for SOC in the recurrent-only, 10.2% versus 6.3% in the recurrent-metastatic, and 15.1% versus 8.8% in the metastatic-only subgroups. DOR was numerically longer with pembrolizumab in all subgroups. CONCLUSION: Pembrolizumab provided numerically longer OS and durable responses in all subgroups compared with SOC, suggesting that patients with previously treated R/M HNSCC benefit from pembrolizumab regardless of recurrence pattern.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.010 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".