Afatinib (A) vs gefitinib (G) as first-line treatment (tx) for patients (pts) with<i>EGFR</i>mutation-positive (<i>EGFR</i>m+) NSCLC: LUX-Lung 7
Bibliographic record
Abstract
Background: The irreversible ErbB family blocker A and the reversible EGFR tyrosine kinase inhibitor (TKI) G are approved for first-line tx of EGFRm+ NSCLC. This Phase IIb trial is the first randomised study to prospectively compare A vs G in this setting. Methods: Patients with stage IIIB/IV EGFRm+ NSCLC received daily A 40mg or G 250mg. Tx continued until disease progression or beyond if deemed beneficial. Co-primary endpoints were progression-free survival (PFS), time to tx failure (TTF; time from randomisation to tx discontinuation) and overall survival (OS). Other endpoints included objective response (OR) and adverse event (AE) incidence and intensity. Results: 319 pts were randomised to A (n=160) or G (n=159). Baseline pt characteristics were similar across tx arms. PFS (HR [95% CI] 0.73 [0.57–0.95]; p=0.017), TTF (0.73 [0.58–0.92]; p=0.007) and OR (70% vs 56%; p=0.008) were significantly improved with A vs G. Improvements were consistent in pt subgroups (e.g. mutation type [Del19/L858R]; race). OS is not yet mature. The most common grade 3 drug-related (DR) AEs were diarrhoea (12%) and rash/acne (9%) with A and elevated ALT/AST with G (8%). DR ILD was reported in 0 pts with A and 4 pts with G. Tx discontinuation due to DR AEs was equal in each arm (6%). Dose reduction of A to 30mg (n=63) or 20mg (n=21) reduced the frequency and intensity of DR AEs but did not compromise PFS (HR [95% CI]: 1.3 [0.9–2.0]; p=0.14) in pts who received <40mg vs ≥40mg. Conclusions: First-line A has superior efficacy to G in EGFRm+ NSCLC pts. AEs were manageable, DR discontinuations were rare, and dose reductions did not impact on efficacy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".