Multi-modality therapy for stage IIIa N2 non-small cell lung cancer: Does the answer lie in the components?
Bibliographic record
Abstract
8537 Background: Neoadjuvant chemoradiation prior to surgery offers excellent locoregional control, while neoadjuvant chemotherapy I meant to offer improved systemic therapy in stage IIIA N2 non-small cell lung cancer (NSCLC). Data are lacking to select the optimal regimen. We compared oncologic outcomes for stage IIIA N2 NSCLC utilizing granular data from three experienced lung cancer treatment centers. Methods: This collaborative retrospective study unites 3 major thoracic centers with differing approaches to IIIA N2 NSCLC. Patients undergoing surgical resection post-neoadjuvant chemotherapy (CxT) or concurrent chemoradiation (CxRT) were included. Primary outcomes were overall and disease- free survival (OS and DFS). Results: Demographic data and outcome data are in Table 1. There were no differences in 5-year OS (CxT 40% vs CxRT 42%, p=0.265) nor in DFS (CxT 30% vs 31%, p=0.275). Recurrence rates (CxT47%vsCxRT48%,p=0.799) and patterns were identical (Local: CxT 10% vs CxRT 8%; and Distant: CxT 30%vsCxRT29%,p=0.764). There was no difference in peri-operative mortality. To address potential bias from differing staging strategies, we excluded patients without invasive mediastinal staging and there were still no differences in OS (CxT 40% vs CxRT 42%, p=0.364) and DFS (CxT 30% vs CxRT 31%, p=0.332) Multivariable analysis identified pnemonectomy (HR1.66,p<0.001) and ypN2 (HR1.84,p<0.001) to be associated with overall survival. Conclusions: Both treatment strategies produce equivalent and better than expected outcomes compared to historical controls for IIIA N2 NSCLC. [Table: see text]
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".