The International Association for the Study of Lung Cancer Thymic Epithelial Tumors Staging Project: Proposal for a Stage Classification for the Forthcoming (Ninth) Edition of the TNM Classification of Malignant Tumors
Bibliographic record
Abstract
INTRODUCTION: A TNM-based system for all types of thymic epithelial tumors was introduced in the eighth edition of the TNM classification of thoracic malignancies. The Thymic Domain of the Staging and Prognostic Factors Committee of the International Association for the Study of Lung Cancer, composed of multispecialty international experts, was charged to develop proposals for the ninth edition. This article outlines the proposed definitions for the T, the N, and the M components and their combination into stage groups. METHODS: A large central database of 11,347 patients with thymic epithelial tumors was assembled thanks to the contribution of the major thymic organizations worldwide and analyses were carried out for the T, the N, and the M components and the stage groups. Overall survival was the outcome measure for patients with completely and incompletely resected tumors, and recurrence for those with complete resection. When the number of patients was sufficient, analyses were performed separately for thymomas, thymic carcinomas, and neuroendocrine thymic tumors. RESULTS: Tumor size is included in the T1 category as T1a (≤5cm) and T1b (>5 cm); the mediastinal pleura is dropped as a T descriptor; invasion of the lung or phrenic nerve is reclassified as T2 (instead of T3). No changes are proposed for the N and the M components from the eighth edition. The stage groups remain the same. CONCLUSIONS: The proposed changes for the ninth edition of the TNM classification set the stage for further progress in the future for these rare tumors.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".