The Society of Thoracic Surgeons Expert Consensus on the Multidisciplinary Management and Resectability of Locally Advanced Non-small Cell Lung Cancer
Bibliographic record
Abstract
BACKGROUND: The contemporary management and resectability of locally advanced lung cancer are undergoing significant changes as new data emerge regarding immunotherapy and targeted treatments. The objective of this document is to review the literature and present consensus among a group of multidisciplinary experts to guide the determination of resectability and management of locally advanced non-small cell lung cancer (NSCLC) in the context of contemporary evidence. METHODS: The Society of Thoracic Surgeon Workforce on Thoracic Surgery assembled a multidisciplinary expert panel composed of thoracic surgeons and medical and radiation oncologists with established expertise in the management of lung cancer. A focused literature review was performed, and expert consensus statements were developed using a modified Delphi process to address 3 major themes: (1) assessing resectability and multidisciplinary management of locally advanced lung cancer, (2) neoadjuvant (including perioperative) therapy, and (3) adjuvant therapy. RESULTS: A consensus was reached on 19 recommendations. These consensus statements reflect updated insights on resectability and multidisciplinary management of locally advanced lung cancer based on the latest literature and current clinical experience, mainly focusing on the appropriateness of surgical therapy and emerging data regarding neoadjuvant and adjuvant therapies. CONCLUSIONS: Despite the complex decision-making process in managing locally advanced lung cancer, this expert panel agreed on several key recommendations. This document provides guidance for thoracic surgeons and other medical professionals in the optimal management of locally advanced lung cancer based on the most updated evidence and literature.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".