First-line afatinib vs gefitinib for patients with EGFR mutation-positive NSCLC (LUX-Lung 7): impact of afatinib dose adjustment and analysis of mode of initial progression for patients who continued treatment beyond progression
Bibliographic record
Abstract
PURPOSE: In the randomized phase IIb LUX-Lung 7 trial, afatinib significantly improved progression-free survival (PFS) and time-to-treatment failure vs gefitinib in patients with treatment-naïve epidermal growth factor receptor mutation-positive non-small cell lung cancer. We report post hoc analyses of tolerability-guided dose adjustment for afatinib and summarize the clinical characteristics of patients who continued afatinib/gefitinib beyond initial radiological progression in LUX-Lung 7. METHODS: Patients received afatinib 40 mg/day or gefitinib 250 mg/day until investigator-assessed progression or beyond if beneficial. In case of selected treatment-related adverse events (TRAEs), the afatinib dose could be reduced by 10-mg decrements to minimum 20 mg (only dose interruptions were permitted with gefitinib). RESULTS: All randomized patients were treated (afatinib, n = 160; gefitinib, n = 159). Sixty-three patients had afatinib dose reduction (< 40 mg/day; 47 within first 6 months). Dose reduction decreased TRAE incidence/severity (before vs after; all grade/grade 3: 100.0%/63.5% vs 90.5%/23.8%). There was no evidence of significant difference in PFS for patients who received < 40 mg/day vs ≥ 40 mg/day for the first 6 months [median: 12.8 vs 11.0 months; hazard ratio 1.34 (95% confidence interval 0.90-2.00)]. Twenty-four and 26 patients continued afatinib and gefitinib, respectively, beyond progression in target lesions; median time from nadir of target lesion diameters to initial progression was 6.7 months and 5.6 months. Of these patients, ~ 70% had objective response or non-complete response/non-progressive disease in non-target lesions at initial progression. CONCLUSIONS: Protocol-defined dose adjustment of afatinib may allow patients to remain on treatment longer, maximizing clinical benefit even in the presence of radiological progression.
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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 | 0.001 | 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".