Afatinib versus erlotinib as second-line treatment of patients (pts) with advanced lung squamous cell carcinoma (SCC): Final analysis of the global phase III LUX-Lung 8 (LL8) trial
Bibliographic record
Abstract
Background: Primary LL8 data showed significantly improved PFS and OS with afatinib compared with erlotinib as second-line treatment in pts with lung SCC, leading to the approval of afatinib in this setting. As previously reported (data cut-off: Apr 2015), PFS (2.6 vs 1.9 months; HR 0.81 [95% CI 0.69–0.96]; p=0.01), objective response rate (ORR; 5.5 vs 2.8%; p=0.06) and disease control rate (DCR; 50.5 vs 39.5%; p=0.002) were higher with afatinib vs erlotinib. PFS and OS benefits on afatinib appeared even greater for pts with ErbB mutation-positive tumours vs ErbB wild-type tumours.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".