Surgical nodal sampling established by Commission on Cancer Standard 5.8 is essential for accurate lung cancer staging

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Objective: Accurate mediastinal staging is critical for the effective treatment of non-small cell lung cancer because lymph node involvement significantly influences prognosis and therapeutic decisions. We sought to evaluate the diagnostic accuracy, limitations, and complementary roles of endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA), cervical mediastinoscopy, and surgical lymph node sampling in mediastinal staging of non-small cell lung cancer. Methods: A systematized literature review was performed using PubMed and national guideline repositories. Studies were included if they reported or provided sufficient data to calculate the negative predictive value (NPV) for EBUS-TBNA, mediastinoscopy, or surgical lymph node sampling. Data were synthesized qualitatively across different clinical scenarios. Results: The pooled (unweighted) NPV of EBUS-TBNA was 93.2% (range, 84.7%-98%). Mediastinoscopy demonstrated a pooled NPV of 93.8% (range, 78.8%-97%), with most false negatives attributable to inaccessible stations. Surgical lymph node sampling yielded a pooled NPV of 92.2% (range, 83.6%-96%) for resected nodal stations, although assessment is limited by variability across studies with inconsistent surgical approaches. These data support the need for systematic intraoperative nodal evaluation to confirm pathologic stage and inform treatment selection. Conclusions: Although EBUS-TBNA is the preferred initial staging modality due to its minimally invasive nature, its diagnostic limitations warrant a low threshold for additional nodal evaluation. Systematic intraoperative lymph node evaluation at the time of surgical resection is indispensable for definitive staging, providing clinically actionable data that influences treatment decisions. Optimal staging of non-small cell lung cancer requires a multidisciplinary, individualized approach that combines modalities based on pretest probability, imaging findings, and patient factors.

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