Postoperative Radiotherapy Option Based on Mediastinal Lymph Node Reclassification for Patients with pN2 Non-small-Cell Lung Cancer
Bibliographic record
Abstract
Background: In this research, we used the mediastinal lymph node reclassification proposed by the International Association for the Study of Lung Cancer (iaslc) to screen for patients with pathologic N2 (pN2) non-small-cell lung cancer (nsclc) who might benefit from postoperative radiotherapy (port). Methods: The study enrolled 440 patients with pN2 nsclc who received complete surgical resection and allocated them to one of three groups: N2a1 (single-station skip mediastinal lymph node metastasis), N2a2 (single-station non-skip mediastinal lymph node metastasis), and N2b (multi-station mediastinal lymph node metastasis). Rates of local recurrence at first recurrence in patients receiving and not receiving port were compared using the chi-square test. Overall (os) and disease-free survival (dfs) were then compared using Kaplan–Meier survival analysis with log-rank test. In addition, the factors potentially influencing os and dfs were analyzed using univariate and multivariate Cox regression. Results: The rate of local recurrence for the N2a2 and N2b groups was significantly lower in patients receiving port (p = 0.044 and p = 0.043 respectively). The log-rank test revealed that, for the N2a1 group, differences in os and dfs were not statistically significant between the patients who did and did not receive port (p = 0.304 and p = 0.197 respectively). For the N2a2 group, os and dfs were markedly superior in patients who received port compared with those who did not (p = 0.001 and p = 0.014 respectively). For the N2b group, os was evidently better in patients who received port compared with those who did not (p = 0.025), but no statistically significant difference in dfs was observed (p = 0.134). Multivariate regression analysis revealed that, in the N2a1 group, port was significantly associated with poor os [hazard ratio (hr): 2.618; 95% confidence interval (ci): 1.185 to 5.785; p = 0.017]; in the N2a2 group, port was associated with improved os (hr: 0.481; 95% ci: 0.314 to 0.736; p = 0.001) and dfs (hr: 0.685; 95% ci: 0.479 to 0.980; p = 0.039). Conclusions: For patients with pN2 nsclc who receive complete resection, port might be beneficial only for patients with single-station non-skip metastasis (N2a2). Patients with single-station skip metastasis (N2a1) and multi-station metastasis (N2b) might not currently benefit from port.
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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".