Response to Second-Line Erlotinib in an EGFR Mutation-Negative Patient with Non-Small-Cell Lung Cancer: Make No Assumptions
Bibliographic record
Abstract
Erlotinib-an oral tyrosine kinase inhibitor (tki) of the epidermal growth factor receptor (egfr)-has commonly been used as a therapeutic option in metastatic non-small-cell lung cancer (nsclc) patients in the second- or third-line treatment setting. A mutation in the EGFR gene (EGFR M+) confers an increased response to this class of drugs. In the first-line setting, use of tkis is restricted to patients having a mutation. The importance of this biomarker has been questioned in subsequent treatment lines.Here, we report a case showing a positive response to erlotinib treatment in the second-line setting. The patient, an elderly male smoker with stage iv nsclc, had a tumour that was EGFR mutation-negative (wild-type EGFR). Based on this clinical case, we discuss the controversy concerning the need for, and impact of, testing for EGFR mutation after first-line treatment.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".