Management of acquired resistance to epidermal growth factor receptor kinase inhibitors in patients with advanced non‐small cell lung cancer
Bibliographic record
Abstract
The widespread adoption of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors for the first-line treatment of patients with advanced EGFR-mutated non-small cell lung cancer has resulted in acquired tyrosine kinase inhibitor resistance becoming a ubiquitous clinical problem. The identification of specific mechanisms of acquired resistance has allowed a better understanding of the biology and natural history of resistant disease, but is only now starting to impact treatment decisions. Strategies for managing acquired resistance in patients with advanced non-small cell lung cancer are complex and must be adapted to the individual characteristics of each patient's cancer. Although combination chemotherapy is the presumed standard of care for most patients, prospective trial data are lacking, highlighting the importance of offering patients participation in clinical trials in this setting. Emerging data from trials of third-generation mutant-specific EGFR kinase inhibitors suggests particular promise with this class of agents.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".