Analysis of overall survival (OS) in two large open-label phase III studies (LUX-Lung 3 [LL3] and LUX-Lung 6 [LL6]) comparing afatinib with chemotherapy (CT) in patients (pts) with advanced non-small cell lung cancer (NSCLC) harboring common (Del19/L858R) epidermal growth factor receptor mutations (EGFR mut)
Bibliographic record
Abstract
Background: Afatinib (A) is an oral, irreversible ErbB family blocker of EGFR, HER2, ErbB3 and ErbB4 signalling. A was compared with cisplatin/pemetrexed (LL3; 345 pts recruited globally) and gemcitabine/cisplatin (LL6; 364 Asian pts) in treatment-naïve pts with EGFR mut stage IIIB/IV NSCLC. A improved progression-free survival (PFS) vs CT in pts with common (Del19/L858R) EGFR mut. Here we present a pooled analysis of mature OS data among such pts. Methods: This analysis included 631/709 pts harboring common EGFR mut (Del19=355, L858R=276) randomized 2:1 to 40 mg A (n=419) or up to 6 cycles of standard CT (n=212). Results: Median follow-up for OS was 36.5 mo and 404 (64%) pts had died at the time of analysis (January 2014). 78% of pts received subsequent systemic therapies (median of 3 regimens); 68% in the CT group received EGFR tyrosine kinase inhibitors and 70% in the A group received CT. OS was significantly improved with A vs CT (median 27.3 vs 24.3 mo, HR=0.81 [CI 0.66, 0.99; p=0.037]). Among Del19 pts the HR=0.59 (CI 0.45, 0.77; p<0.001) and in L858R pts the HR=1.25 (CI 0.92, 1.71; p=0.160). Updated PFS and safety findings were consistent with earlier primary reports. Conclusions: This pooled analysis reveals that first-line A improves OS by 3 mo in pts with advanced NSCLC harboring common EGFR mut (Del19/L858R) compared with CT. This is the first analysis to show that genotype-directed therapy for EGFR mut pts can improve survival.
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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 | 0.011 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".