Central tumor location and presence of occult lymph node metastasis in cT1N0M0 NSCLC
Bibliographic record
Abstract
Background and Objective: Recent guidelines on non-small cell lung cancer (NSCLC) propose that tumors smaller than 3 cm, centrally located, without evidence of positive lymph nodes on computed tomography (CT) and/or positron emission tomography (PET) require invasive mediastinal staging by surgical or needle technique before further treatment. The objective of this study was to identify a definition of central location for cT1N0M0 NSCLC that best discriminates the risk of occult mediastinal nodal disease (pN2). Methods: Our institutional pulmonary oncology database was researched for the 2014 to 2017 period for all patients who had cT1N0M0 probable NSCLC after CT and PET-CT. Patients who did not undergo invasive lymph node evaluation were excluded. Two definitions of central location were explored 1) inner third or 2) inner two thirds of the lung field, using a model of concentric circles originating from the hilum. Results: Two hundred and ten cT1N0M0 NSCLC were included in our study after applying exclusion criteria. Twenty-one (10%) and sixty-three (30%) tumors were respectively considered central using the inner third and the inner two-thirds definitions. Central location was not associated with an increased incidence of pN2 using either definition (p = 0.24). Occult pN2 was found in 5.2% of patients (0-4.8% of central tumors versus 5.4-5.8% of peripheral tumors). Higher SUV and female gender were associated with more occult lymph node metastasis. Conclusion: None of the definitions of central location explored were associated with increased prevalence of pN2. pN2 prevalence was low in cT1N0M0 NSCLC and necessity for invasive mediastinal staging in this population should be questioned.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".