Network meta-analysis of pembrolizumab as monotherapy and in combination with chemotherapy for first-line treatment of recurrent or metastatic head and neck squamous cell carcinoma
Bibliographic record
Abstract
Pembrolizumab monotherapy or in combination with chemotherapy is approved as first-line treatment in recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC) based on improved overall survival (OS) versus EXTREME regimen in the KEYNOTE-048 trial. The clinical outcomes of pembrolizumab were compared with other recommended first-line treatments in R/M HNSCC in this study through a Bayesian network meta-analysis. A systematic literature review was conducted in July 2022, from which six trials that matched the KEYNOTE-048 patient eligibility criteria were included in the network. The OS and progression-free survival (PFS) outcomes were compared in the approved pembrolizumab indication (i.e., total population for pembrolizumab in combination with chemotherapy and combined positive score [CPS] ≥ 1 population for pembrolizumab monotherapy). A significant OS improvement was observed for pembrolizumab in combination with chemotherapy and pembrolizumab monotherapy versus EXTREME regimen (hazard ratio, 95% credible interval: 0.72, 0.60-0.86; 0.73, 0.60-0.88), platinum+5- FU (0.58, 0.43-0.76; 0.58, 0.44-0.78), and platinum+paclitaxel (0.53, 0.35-0.79; 0.53, 0.35-0.81), respectively. A non-significant numeric trend in OS improvement was observed versus the TPEx regimen. PFS was comparable with most first-line treatments and was improved versus platinum+5-FU (0.48, 0.36-0.64; 0.59, 0.45-0.79). Additional analyses in higher CPS subgroups also showed consistent results. Overall, our study results showed an improvement in OS outcomes versus alternative first-line treatments, consistent with the findings of the KEYNOTE-048 trial. These data support using pembrolizumab as a suitable firstline treatment option in R/M HNSCC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".