Optimal Adjuvant Therapy for Non-Small Cell Lung Cancer—How to Handle Stage I Disease
Bibliographic record
Abstract
The standard of care for resected stage II-IIIA non-small cell lung cancer (NSCLC) now includes adjuvant chemotherapy based on the results of three phase III studies using cisplatin-based regimens--the International Adjuvant Lung Trial, the National Cancer Institute of Canada JBR.10 trial, and the Adjuvant Navelbine International Trialist Association trial. The role of adjuvant chemotherapy for stage I disease remains controversial. A recent meta-analysis (the Lung Adjuvant Cisplatin Evaluation) showed potential harm with the addition of adjuvant cisplatin for stage IA disease and no survival benefit for this modality in stage IB disease. Updated results from the Cancer and Leukemia Group B 9633 trial, the only trial to focus exclusively on stage IB patients, no longer show a statistically significant survival benefit from adjuvant chemotherapy in this population, except for the subgroup of patients with larger tumors. It may be that trials have been underpowered to detect a small benefit for patients with stage IB disease, or there may really not be benefit to adding adjuvant therapy for this stage of disease. Additional markers, such as tumor size or the presence or absence of certain tumor proteins like ERCC1, may help to determine which patients with resected stage I NSCLC may benefit from adjuvant chemotherapy. Strategies such as inhibition of angiogenesis pathways and the epidermal growth factor receptor are under exploration.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".