Expert Consensus Statement on Optimal Approach to Lobectomy for Non-Small Cell Lung Cancer
Bibliographic record
Abstract
A systematic review and meta-analysis to help define the optimal approach for lobectomy for non-small cell lung cancer was undertaken.Articles comparing thoracotomy (open), multi-port Video-assisted thoracic surgery (mVATS), robotic VATS (rVATS), and uniportal VATS (uVATS) were scrutinized and evidence-based statements using the American College of Cardiology/American Heart Association clinical practice guideline recommendations made. 1 A total of 145 studies met the inclusion criteria and the following 15 evidence-based statements achieved consensus.2 The statements are as follows: QuestionsDoes VATS result in better survival outcomes than open lobectomy?What is the best minimally invasive surgery (MIS) approach with respect to survival?Statements 1. mVATS lobectomy may be associated with improved overall survival compared to open lobectomy.Class IIB (Level C-LD) 2. mVATS may have similar disease-free survival when compared to open lobectomy.Class IIB (Level C-LD) 3. mVATS may be associated with a lower recurrence rate, primarily related to distant recurrence when compared to open lobectomy.Class IIB (Level C-LD) 4. rVATS has no difference in overall survival and recurrence when compared to mVATS lobectomy.Class IIB (Level C-EO)
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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 | 0.025 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".