Afatinib With Pembrolizumab for Treatment of Patients With Locally Advanced/Metastatic Squamous Cell Carcinoma of the Lung: The LUX-Lung IO/KEYNOTE 497 Study Protocol
Bibliographic record
Abstract
BACKGROUND: Afatinib is a selective, irreversible ErbB family blocker that has shown survival benefit in lung squamous-cell carcinoma (SCC) patients. Pembrolizumab, a humanized immunoglobulin G4 monoclonal antibody to the programmed cell death 1 (PD-1) receptor, has also shown survival benefit in lung SCC. Concurrent inhibition of the PD-1 and epidermal growth factor receptor (EGFR) pathways represents a rational approach to improve responses and delay the onset of treatment resistance in lung SCC. TRIAL DESIGN: This phase II, open-label, single-arm study (NCT03157089) is designed to assess the efficacy and safety of afatinib in combination with pembrolizumab in patients with stage IIIB/IV lung SCC that has progressed during/after first-line platinum-based chemotherapy. Eligible patients must have ≥1 target lesion (as per Response Evaluation Criteria in Solid Tumors version 1.1) and must have not received previous immune checkpoint inhibitor/EGFR-targeted therapy. The recommended phase II dose (RP2D) and safety profile will be determined during a safety run-in with oral afatinib (starting dose, 40 mg/d) with intravenous pembrolizumab (200 mg every 3 weeks). In the main study, all patients will receive afatinib at the RP2D with pembrolizumab until disease progression, unacceptable toxicity, or for up to 35 cycles. The primary end point is objective response (complete + partial response). Other end points include disease control, duration of objective response, progression-free survival, overall survival, tumor shrinkage, RP2D, and pharmacokinetics. Exploratory biomarker analysis will be performed. This study is being conducted in the United States, Spain, France, South Korea, and Turkey. Enrollment commenced in September 2017, with a target of 50 to 62 patients.
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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) | 0.001 | 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".