ArticleLung cancer (Amsterdam, Netherlands)2026
Utilization of invasive mediastinal nodal staging and prevalence of occult nodal disease in patients with synchronous primary lung cancers.
Article in Lung cancer (Amsterdam, Netherlands), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundGuidelines recommend invasive mediastinal nodal staging (IMNS) for patients with synchronous primary lung cancer (SPLC) who are candidates for curative resection. We investigated the prevalence of occult nodal disease and selective use of IMNS in patients with SPLC.
methodsPatients with SPLC suspected on preoperative imaging who underwent resection from 2000 to 2022 were included. Exclusion criteria included metachronous and recurrent lung cancer, cStage III-IV, carcinoid histology, absence of preoperative PET/CT, and receipt of neoadjuvant therapy. Univariable analysis identified clinicopathologic risk factors for occult nodal disease. Proposed criteria for identifying a patient at low risk for occult nodal disease were as follows: all primary tumors are peripheral, subsolid, ≤3 cm on preoperative CT, and have a maximum standardized uptake value (SUVmax) < 3.6, and lymph nodes must be PET negative.
resultsOf 484 eligible patients, only 19% (n = 90) underwent IMNS. After excluding patients with clinical nodal disease on IMNS and/or imaging, 472 patients remained, of which 14% (68/472) had occult nodal disease, with 5.9% (28/472) having occult N2 disease. Patients with occult nodal disease had dominant tumors with a higher SUVmax (median, 6.0 vs. 3.2; p < 0.001), central location (31% vs. 17%; p = 0.009) and solid appearance (76% vs. 46%; p < 0.001). Our proposed criteria categorized 21% of patients with complete data (96/449)as low risk for occult nodal disease(sensitivity = 24.4%, specificity = 96.9%, positive predictive value = 97.9%, negative predictive value = 17.6%).
conclusionsThe decision to pursue IMNS in patients with SPLC should be individualized using imaging characteristics including central location, solid-appearance, tumor size, and SUVmax.
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