Benefit from Adjuvant TKIs Versus TKIs Plus Chemotherapy in EGFR-Mutant Stage III-pN2 Lung Adenocarcinoma
Bibliographic record
Abstract
Background: Recent studies have demonstrated benefits from adjuvant tyrosine-kinase inhibitors (TKIs) compared with chemotherapy in non-small cell lung cancer. We launched a multi-center retrospective study to evaluate the efficacy and toxicity of adjuvant TKIs with or without chemotherapy in epidermal growth factor receptor (EGFR)-mutant stage III-pN2 lung adenocarcinoma. Methods: Two hundred and seventy-four consecutive cases with stage III-pN2 lung adenocarcinoma and complete resection have been investigated. Clinic-pathologic characteristics, adjuvant treatments, long-term survivals, and toxicities were documented. Risk factors of distant metastasis-free survival (DMFS), disease-free survival (DFS), and overall survival (OS) were evaluated. Results: There were 52 (19.0%) patients treated with adjuvant TKIs alone, 199 (72.6%) with adjuvant chemotherapy alone, and 23 (8.4%) with both. After a median follow-up time of 29 months, the two-year DMFS, DFS, and OS was 61.2%, 54.1%, and 91.2%, respectively. According to univariable analyses, the risk factors were lymphovascular invasion (p < 0.001), extranodal extension (p = 0.005), and adjuvant systemic therapy (p = 0.006) for DMFS, EGFR mutation type (p = 0.025), lymphovascular invasion (p = 0.013), extranodal extension (p = 0.004), and adjuvant systemic therapy (p < 0.001) for DFS, and EGFR mutation type (p < 0.001) for OS. Multivariable analyses indicated that the independent prognostic factors were adjuvant systemic therapy (TKIs vs. TKIs+chemotherapy, Harzard ratio (HR) = 0.40; p = 0.036; TKIs vs. chemotherapy, HR = 0.38; p = 0.004), lymphovascular invasion (yes vs. no, HR = 2.22; p = 0.001) for DMFS, and adjuvant systemic therapy (TKIs vs. TKIs+chemotherapy, HR = 0.42; p = 0.034; TKIs vs. chemotherapy, HR = 0.33; p < 0.001) for DFS. No significant difference was found in the incidence of Grade 3–4 toxicities between groups (p = 0.445). Conclusions: Adjuvant TKIs might be a beneficial choice compared with adjuvant chemotherapy or combination systemic treatments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".