Afatinib in patients with metastatic <i>HER2</i>-mutant lung cancers: An international multicenter study.
Bibliographic record
Abstract
9071 Background: Human epidermal growth factor 2 ( HER2, ERBB2) mutations have been identified as oncogenic drivers in 3% of lung cancers. Afatinib is an irreversible tyrosine kinase inhibitor of HER1 (EGFR), HER2 and HER4 and has been described in case reports to have activity in HER2-mutant lung cancers. However, there is little data to inform the clinical use of afatinib. Methods: We reviewed patients with metastatic HER2-mutant lung cancers treated with afatinib among 7 institutions between 2009 and 2016. The primary endpoint was investigator assessed overall response rate using RECIST v1.1. Other data collected included types of HER2mutations, duration of afatinib treatment and overall survival. Results: We identified 27 patients with metastatic HER2-mutant lung cancers treated with afatinib. Median age at diagnosis was 63 (range 40 to 84); majority were men (n = 16; 59%) and never-smokers (n = 18; 67%). All tumors were adenocarcinomas, and the majority were Stage IV at initial diagnosis (n = 16; 59%). A 12-base pair (bp) in-frame insertion YVMA in exon 20 (p.A775_G776insYVMA) was present in 16 patients (59%). In addition, there were three 9-bp insertions, two 3-bp insertions and two single bp substitutions (L755F and D769H) in exon 20; two single bp substitutions (S310F) in exon 8; one exon 17 V659E mutation; and one single-nucleotide polymorphism (Ile655Val). Median duration on afatinib was 2 months (range 1 to 27); median line of prior treatment was 3 (range 1 to 6). Eight patients had previously received trastuzumab prior to afatinib and one concurrently with afatinib. Overall response rate was 15% (n = 4; 95% CI 4 to 34%); the four partial responses lasted 5, 5, 6 and 10 months. The 3 longest partial responders had a 12-bp insertion in exon 20 (YVMA); the remaining partial responder had a 9-bp insertion in exon 20. Median overall survival from diagnosis date of metastatic disease was 23 months (95% CI 18 to 62). Conclusions: Afatinib produced partial responses in 15% of patients with metastatic HER2-mutant lung cancers, including insertion YVMA. Our findings confirm the activity of afatinib and provide data supporting a framework for its use in the care of patients with HER2-mutant lung cancers.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".