Erlotinib in the treatment of non-small cell lung cancer
Bibliographic record
Abstract
Inhibition of the epidermal growth factor receptor is one of the most promising novel therapeutic strategies to be used in the treatment of patients with non-small cell lung cancer. A number of compounds that target the epidermal growth factor receptor are in an advanced stage of clinical development including both antibodies directed against the receptor and small molecule inhibitors of epidermal growth factor receptor tyrosine kinase activity. This drug profile focuses on the development of erlotinib, an orally available inhibitor of epidermal growth factor receptor tyrosine kinase. Results of clinical trials are reviewed, two trials of erlotinib in combination, one with paclitaxel and carboplatin, the other with gemcitabine and cisplatin, and the National Cancer Institute of Canada--Clinical Trials Group BR21, the first study to demonstrate a survival benefit for this class of compound in non-small cell lung cancer. The future role of erlotinib in the management of patients with non-small cell lung cancer is also discussed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".