Surgery for early non-small cell lung cancer with preoperative erlotinib (SELECT): A correlative biomarker study.
Bibliographic record
Abstract
7516 Background: Erlotinib has demonstrated major activity in EGFR mutation positive NSCLC, but may also benefit those with wild-type tumours. We conducted a single-arm trial of pre-operative erlotinib in early stage NSCLC to assess radiologic and functional response as well as correlation with known and investigational biomarkers. Methods: Patients with clinical stage IA-IIB NSCLC received erlotinib 150 mg daily for 4 weeks followed by surgical resection. Tumor response was assessed using pre- and post-treatment CT and PET imaging. Pharmacodynamic changes were assessed through comparison of pre- and post-treatment tumour samples (including Sequenom MassARRAY analysis) and measurement of circulating markers/ligands for EGFR activation (TGF-α, amphiregulin, epiregulin, EGFR SNP, EGFR ECD). Secondary endpoints included pathological response, toxicity and progression-free survival. Results: Twenty-five patients were enrolled; 22 received erlotinib treatment with a median follow up of 4.4 years (range 2.2 to 6.4 years). Histology was predominantly adenocarcinoma (14) with smaller numbers of squamous carcinoma (7) and large cell carcinoma (1). PET response (25% SUV reduction) was observed in 2 patients (9%), both with confirmed squamous carcinoma histology. All patients met criteria for stable disease by RECIST and several experienced minor radiographic regression with histologic findings of fibrosis/necrosis, including 2 with squamous histology. The presence of an EGFR exon 19 deletion was detected in one adenocarcinoma case; the patient experienced a minor radiographic response to treatment. Genotyping, functional protein assays and ligand analysis are ongoing. Conclusions: Erlotinib appears to demonstrate some activity in patients with squamous histology. While EGFR mutations have been infrequently demonstrated in squamous NSCLC, the potential exists for other biomarkers predictive of benefit. Clinical trial information: NCT00462995.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".