The role of bronchoscopy in the diagnosis of early lung cancer: a review
Bibliographic record
Abstract
Lung cancer is the leading cause of cancer-related deaths worldwide with an overall 5-year survival rate of 17% after diagnoses. Indeed many patients tend to have a very poor prognosis, due to being diagnosed at an advanced stage. Conversely patients who are diagnosed at an early stage have a 5-year survival >70%, indicating that early detection of lung cancer is crucial to improve survival. Although flexible bronchoscopy is a relatively non-invasive procedure for patients suspected of having lung cancer, only 29% of carcinoma in situ (CIS) and 69% of microinvasive tumors were detectable using white light bronchoscopy (WLB) alone. As a result, in the past two decades, new bronchoscopic techniques have been developed to increase the yield and diagnostic accuracy, such as autofluorescence bronchoscopy (AFB), narrow band imaging (NBI) and high magnification bronchovideoscopy (HMB). However, due to the low specificity and the limitation to detect only proximal bronchial tree, new probe-based technologies have been introduced: radial endobronchial ultrasound (R-EBUS), optical coherence tomography (OCT), confocal laser endomicroscopy (CLE) and laser Raman spectroscopy (LRS). To date, although tissue biopsy remains the gold standard for diagnosing malignant/premalignant airway disease and some techniques are still investigational, bronchoscopic technologies can be considered the safest and most accurate tools to evaluate both central and distal airway mucosa.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".