Talimogene Laherparepvec and Pembrolizumab in Recurrent or Metastatic Squamous Cell Carcinoma of the Head and Neck (MASTERKEY-232): A Multicenter, Phase 1b Study
Bibliographic record
Abstract
PURPOSE: The prognosis for patients with recurrent or metastatic head and neck squamous cell carcinoma (R/M HNSCC) is poor, and only a minority of patients benefit from checkpoint immunotherapy. Talimogene laherparepvec (T-VEC), an oncolytic immunotherapy approved for advanced melanoma, in combination with pembrolizumab may yield enhanced antitumor activity over either agent alone. PATIENTS AND METHODS: This was a phase Ib/III, multicenter trial testing intratumoral T-VEC combined with intravenous pembrolizumab in R/M HNSCC refractory to platinum-based chemotherapy. For phase Ib, primary endpoint was incidence of dose-limiting toxicity (DLT). Key secondary endpoints included objective response rate and progression-free survival per irRECIST, overall survival, and safety. RESULTS: Thirty-six patients were enrolled into the phase Ib study. The data cut-off date was August 28, 2018. Median follow-up was 5.8 months (range, 0.3-24.2). One DLT of T-VEC-related fatal arterial hemorrhage was reported. Twenty (55.6%) and 21 (58.3%) patients experienced adverse events (AE) related to T-VEC and pembrolizumab, respectively. Besides the DLT, there were no treatment-related fatal AEs. A confirmed partial response was observed in 5 (13.9%) patients. Ten (27.8%) patients were unevaluable for response due to early death. Median PFS and OS were 3.0 months [95% confidence interval (Cl), 2.0-5.8] and 5.8 months (95% Cl, 2.9-11.4), respectively. CONCLUSIONS: The combination of T-VEC and pembrolizumab demonstrated a tolerable safety profile in R/M HNSCC. The efficacy with the combination was similar to that with pembrolizumab monotherapy in historical HNSCC studies. Phase III part of this study was not further pursued (ClinicalTrials.gov Identifier: NCT02626000).
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".