Characterizing phantom lymph node collection during curative-intent resection of non−small cell lung cancer

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Authors: Ahmed Ghani, Nahom Seyoum, Daniel B. Eaton, Sara Malone, Su-hsin Chang, Yan Yan, Ana A. Baumann, Theodore S. Thomas, Martin W. Schoen, Molly C. Tokaz, Steven Tohmasi, Nikki Rossetti
+8 more Mayank R. Patel, Whitney S. Brandt, Daniel Kreisel, Ruben G. Nava, Bryan F. Meyers, Benjamin D. Kozower, Varun Puri, Brendan T. Heiden
Cited by: 1
References: 17

Abstract

OBJECTIVES: Phantom lymph node collection, defined as intraoperative sampling of tissue presumed to be nodal that, on pathologic review, proves to be non-nodal, is a previously understudied outcome in thoracic surgery. This study aimed to quantify its incidence, identify associated factors, and assess its relationship with cancer-specific outcomes. METHODS: We conducted a retrospective cohort study using a meticulously curated Veterans Health Administration dataset of patients undergoing curative-intent non-small cell lung cancer resection between 2018 and 2024. Our primary outcomes included frequency of phantom lymph node collection, along with covariates independently associated with it. Secondary outcomes were overall survival and recurrence-free survival. RESULTS: A total of 2972 veterans were included in this cohort. Phantom lymph node collection occurred in 327 (11.0%) patients. On multivariable analysis, phantom lymph node collection was more likely with lower-lobe tumors (odds ratio, 1.45; 95% CI, 1.13-1.88), and less likely among patients who received guideline-concordant nodal sampling (≥3 N2 and ≥1 N1 nodal stations) (odds ratio, 0.56; 95% CI, 0.43-0.74). Notably, phantom lymph node collection was not associated with overall (hazard ratio, 0.96; 95% CI, 0.77-1.19) or recurrence-free survival (hazard ratio, 0.86; 95% CI, 0.68-1.08). CONCLUSIONS: Phantom lymph node collection is common during curative-intent resection of early-stage lung cancer. Although not prognostic, its association with guideline-concordant sampling highlights it as a potential target for surgical quality improvement initiatives.

Fields of Study & Subjects

Lung Cancer Diagnosis and Treatment Breast Cancer Treatment Studies Radiomics and Machine Learning in Medical Imaging

Publication details

Journal / source
Journal of Thoracic and Cardiovascular Surgery
Publisher
Elsevier BV
Volume
171
Issue
6
Pages
1332–1338.e3
Publication date
28 January 2026
Language
EN