Lymph Node Sampling Patterns and Completeness of Staging During Systematic Mediastinal Lymph Node Staging in Patients with Locally Advanced Non-Small-Cell Lung Cancer: A Post Hoc Analysis from the SEISMIC Study

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Authors: Kanishka Rangamuwa, Ashleigh Witt, Joseph M. Curran, Gargi Kothari, Neil Wallace, Nicholas Hardcastle, Shaun W. Yo, Farzad Bashirdazeh, Phan Nguyen, Barton R. Jennings, David I. Fielding, L. Crombag
+5 more Kazuhiro Yasufuku, Jouke Tabe Annema, David Ost, Shankar Siva, Daniel Steinfort
Cited by: 1
References: 28

Abstract

Introduction: Systematic endoscopic mediastinal lymph node (LN) staging in early stage non-small-cell lung cancer (NSCLC) is widely recommended for optimal pre-operative staging due to imperfect accuracy of PET/CT. The SEISMIC study utilized synoptic reporting of findings during systematic endoscopic staging to inform radiotherapy planning in patients with locally advanced NSCLC and established a significant rate of discordance between PET-identified extent of disease and observed findings following EBUS. International guidelines recommend systematic LN staging in patients with clinical nodal stage (cN) 1–3 disease as a quality indicator, though performance metrics for quality assessment of systematic endoscopic mediastinal staging in NSCLC have not been described. Methods: A post hoc analysis of 155 participants with locally advanced NSCLC recruited to the SEISMIC study who underwent systematic endoscopic mediastinal staging, with sampling of all LN ≥ 6 mm, prior to planning of radical or high-dose palliative radiation, was completed. Synoptic procedural reports and pre-procedure PET imaging were examined to determine the number of LN sampled, as well as the number of radiologically normal LN ( 6 mm at higher station than the highest LN identified by PET not sampled endoscopically, confirming a high rate of complete mediastinal assessment. Conclusions: Quality of systematic staging in the SEISMIC study was high. Synoptic reporting supports high quality systematic endoscopic mediastinal LN staging in NSCLC and enables performance monitoring of systematic EBUS staging. Novel quality metrics are proposed for quality assessment, and consistent use of these may encourage more extensive LN sampling.

Fields of Study & Subjects

Lung Cancer Diagnosis and Treatment Radiomics and Machine Learning in Medical Imaging Esophageal Cancer Research and Treatment

Publication details

Journal / source
Cancers
Publisher
MDPI AG
Volume
18
Issue
11
Pages
1766–1766
Publication date
28 May 2026
Language
EN