Lymphatic invasion acts as a 'hidden risk factor': four-fold increased mortality risk in early-Stage (TNM Stage i, N0) non-small cell lung cancer

Abstract

Despite advances in the TNM staging system, prognostic heterogeneity persists in early-stage non-small cell lung cancer (NSCLC). Lymphatic invasion (LI) is a known marker of aggression, but its independent significance in the critical, low-risk Stage I, N0 subgroup—typically ineligible for adjuvant therapy—remains poorly defined. We hypothesized that LI acts as a powerful, yet hidden, risk factor in this highly favourable cohort. Methods: This retrospective cohort study included 988 consecutive patients who underwent curative anatomical resection for NSCLC. All patients underwent complete resection with pathologically confirmed negative surgical margins (R0 resection). Cases were staged according to the 9th Edition of the TNM Classification of Malignant Tumours (TNM-9) and grouped as LI-positive or LI-negative. A critical subgroup analysis focused on 347 truly low-risk patients (TNM Stage I, N0, no vascular or pleural invasion). Overall survival (OS) was evaluated using the Kaplan–Meier method and multivariable Cox proportional hazards models. Results: In the entire cohort (n = 988), LI was present in 40.9% of cases. LI positivity was an independent predictor of worse OS in multivariable analysis (HR: 1.520, 95% CI: 1.004–2.301, p = 0.048). In the low-risk subgroup (n = 347), the presence of LI resulted in a drastic survival divergence, with 5-year OS declining from 96.1% (LI-negative) to 83.8% (LI-positive). Multivariable analysis confirmed LI as an independent adverse prognostic factor in this subgroup (HR: 4.002, 95% CI: 1.567–10.221, p = 0.004). Conclusions: Lymphatic invasion is a robust, independent adverse prognostic factor in resected NSCLC. LI may identify a subset of early-stage N0 NSCLC patients who warrant closer postoperative surveillance and prospective evaluation for adjuvant treatment strategies. Validation in prospective cohorts is required before LI can be formally integrated into staging algorithms or treatment guidelines.