A standard for hilar and intrapulmonary lymph node dissection and pathological examination in early non-small cell lung cancer
Bibliographic record
Abstract
BACKGROUND: There is considerable variation in the staging of lymph nodes (LNs) as part of tumor, node, metastasis (TNM) staging of non-small cell lung cancer (NSCLC). A new dissection and pathological examination standard for hilar and intrapulmonary LNs needs to be established for patients with early-stage T1-3N0M0 NSCLC. METHODS: This study involved 3,002 patients with T1-3N0M0 NSCLC who underwent radical lobectomy or total pneumonectomy in the thoracic departments of 11 Chinese institutions between January 1999 and October 2013. The Cox model was applied for univariate and multivariate analyses in the examination of station 10, 11 LN and station 12, 13, 14 LN. A hilar and intrapulmonary standard (HI standard) was then established based on univariate and multiple-factor analyses conducted using the Cox model. RESULTS: Among the 3,002 patients enrolled in the study, 2,609 underwent at least one examination of station 10, 11 LN (A1), while 393 did not undergo examination of station 10, 11 LN (A0). The A0 and A1 groups had 5-year survival rates of 76% and 80%, respectively (P=0.018). Further, 1,764 patients underwent at least one examination of station 12, 13, 14 LN (B1), while 1,238 patients did not (B0). The B0 and B1 groups had 5-year survival rates of 77% and 82%, respectively (P=0.008). In total, 1,269 patients attained the HI standard (C1), and 1,733 did not (C0). The C0 and C1 groups had 5-year survival rates of 77% and 83%, respectively (P<0.001). CONCLUSIONS: The HI standard can improve both the prognosis and survival rates of patients with T1-3N0M0 NSCLC. This will provide important guidance for pulmonary LN dissection and pathological examination in NSCLC cases.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".