A Phase 1b/2 Study of Alpelisib in Combination with Cetuximab in Patients with Recurrent or Metastatic Head and Neck Squamous Cell Carcinoma
Bibliographic record
Abstract
BACKGROUND: Alpelisib in combination with cetuximab showed synergistic anti-tumour activity in head and neck squamous cell carcinoma (HNSCC) models. OBJECTIVES: The recommended phase 2 dose (RP2D) was determined in a phase 1b dose-escalation study. Phase 2 evaluated anti-tumour activity with a randomised part in cetuximab-naïve patients and a non-randomised part in cetuximab-resistant patients. PATIENTS AND METHODS: Alpelisib was administered in 28 d cycles as whole tablets, suspension from crushed tablets or suspension from dispersible tablets in patients with platinum-resistant, recurrent/metastatic HNSCC. RESULTS: The RP2D determined for alpelisib was 300 mg/d. Alpelisib-cetuximab achieved an overall response rate of 25% and 9.9% and disease control rate of 75% and 43.7% in phase 1b and phase 2 studies, respectively. Median progression-free survival (PFS) per central review was 86 d for combination treatment and 87 d for cetuximab monotherapy (unadjusted HR 1.12; 95% CI 0.69-1.82; P > 0.05). When adjusted for baseline covariates [sum of longest diameters from central data, haemoglobin and white blood cell (WBC), the results favoured combination treatment (adjusted HR 0.54; 95% CI 0.30-0.97; P = 0.039). PFS per investigator assessment resulted in an unadjusted HR of 0.76 (95% CI 0.49-1.19; P > 0.05) favouring combination treatment. The median PFS in cetuximab-resistant patients was 3.9 months. CONCLUSIONS: The addition of alpelisib to cetuximab did not demonstrate a PFS benefit in cetuximab-naïve patients with advanced HNSCC. The alpelisib-cetuximab combination showed moderate activity in cetuximab-resistant patients, with a consistent safety profile. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT01602315; EudraCT 2011-006017-34.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".