Systematic Endobronchial Ultrasound-guided Mediastinal Staging Versus Positron Emission Tomography for Comprehensive Mediastinal Staging in NSCLC Before Radical Radiotherapy of Non-small Cell Lung Cancer
Bibliographic record
Abstract
Despite known limitations of positron emission tomography (PET) for mediastinal staging of non-small cell lung cancer (NSCLC), radiation treatment fields are generally based on PET-identified disease extent. However, no studies have examined the accuracy of FDG-PET/CT on a per-node basis in patients being considered for curative-intent radiotherapy in NSCLC.In a prospective trial, patients with NSCLC being considered for definitive thoracic radiotherapy (± systemic chemotherapy) underwent minimally invasive systematic mediastinal evaluation with endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) following noninvasive staging with integrated PET-CT.Thirty patients underwent EBUS-TBNA, with TBNA performed from a mean 2.5 lymph node (LN) stations per patient (median 3, range 1-5). Discordant findings between PET-CT and EBUS-TBNA were observed in 10 patients (33%, 95% CI 19%-51%). PET-occult LN metastases were demonstrated by EBUS in 4 patients, whereas a lesser extent of mediastinal involvement, compared with FDG-PET, was demonstrated by EBUS in 6 patients, including 2 patients downstaged from cN3 to pN2. LNs upstaged by EBUS were significantly smaller than nodes downstaged by EBUS, 7.5 mm (range 7-9) versus 12 mm (range 6-21), P = 0.005.A significant proportion of patients considered for definitive radiotherapy (+/-chemotherapy) undergoing systematic mediastinal evaluation with EBUS-TBNA in this study have an extent of mediastinal NSCLC involvement discordant with that indicated by PET-CT. Systematic EBUS-TBNA may aid in defining the extent of mediastinal involvement in NSCLC patients undergoing radiotherapy. Systematic EBUS-TBNA has the potential to contribute significantly to radiotherapy planning and delivery, by either identifying occult nodal metastases, or demonstrating FDG-avid LNs to be disease-free.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".