American Association for Bronchology and Interventional Pulmonology (AABIP) Evidence-Based Guidelines on Bronchoscopic Diagnosis and Staging of Lung Cancer
Bibliographic record
Abstract
BACKGROUND: Lung cancer remains a predominant cause of cancer-related deaths worldwide, and there are notable geographic and institutional differences in both diagnostic and staging approaches. To address this, the American Association for Bronchology and Interventional Pulmonology (AABIP) convened a multidisciplinary committee to craft evidence-based and evidence-informed recommendations for diagnosing peripheral pulmonary nodules and performing convex probe endobronchial ultrasound (CP-EBUS)-guided mediastinal staging. METHODS: A modified Delphi method guided the creation and refinement of 9 Population, Intervention, Comparator, Outcome (PICO) questions. A systematic literature review, updated through March 2023, served as the basis for drafting recommendations. The panel used the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach to assess the quality of evidence and relied on National Institute for Health and Care Excellence (NICE) language to express the strength of each recommendation. Where suitable, meta-analyses were completed; otherwise, systematic reviews and consensus among experts provided the evidence for guidance. RESULTS: Nine recommendations were ultimately proposed: 6 were supported by meta-analyses and 3 by systematic reviews. The topics include comparing diagnostic yield and complication rates between peripheral bronchoscopy and transthoracic needle biopsy, the use of multiple biopsy instruments and the role of rapid on-site evaluation (ROSE) during peripheral bronchoscopy, and best practices for CP-EBUS-guided mediastinal staging. Several critical considerations emerged, such as lesion size, evolving technologies in bronchoscopy, and the importance of both available resources and local expertise. CONCLUSION: These guidelines aim to standardize and streamline recommendations for the bronchoscopic diagnosis and staging of lung cancer. Since rapid technological progress and observational data play significant roles in this field, ongoing research and evidence updates will be vital to refining best practices. Clinicians are advised to tailor these recommendations according to local circumstances, the unique needs of their patients, and any new findings as they develop.
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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 | 0.035 | 0.072 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".