Optimal Margin for Sublobar Resection of Invasive Lung Adenocarcinoma Presenting as Mixed Ground-Glass Nodules.

Li, Hao; Pezeshkian, Fatemehsadat; Sugarbaker, Evert; Mazzola, Emanuele; Byrne, Suzanne C; Hooshmand, Fatemeh; Bueno, Raphael; Hammer, Mark M et al. · Ann Thorac Surg · 2026

retrospective_cohort · Level III

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Abstract

Lung adenocarcinomas presenting as mixed ground-glass nodules (GGNs) are commonly treated by sublobar resection with favorable survival, but the optimal margin remains unclear. We retrospectively reviewed patients with cT1 (≤3 cm) GGNs who underwent curative sublobar resection (January 2012-December 2020) and had invasive adenocarcinoma confirmed. Patients with uncertain/positive margins or positive lymph nodes were excluded. Margin distance was pathologically defined as the shortest distance from tumor edge to resection margin. Cox proportional hazards regression, Kaplan-Meier, and competing-risk analysis were used to assess the relationship between the margin-to-tumor diameter ratio (MTR) and margin-to-solid component ratio (MSR) and locoregional recurrence-free survival (LRFS). Optimal cutoffs for LRFS prediction were identified using recursive classification tree analysis. Among 208 patients (median follow-up, 64 months), median tumor, solid component, and margin sizes were 18.0, 6.25, and 12.0 mm, respectively. Recursive partitioning identified MTR as most predictive, with an optimal cutoff of ∼0.174. MTR and MSR were the top influential predictors and strongly correlated through a second-degree polynomial model. Patients with MTR ≥0.2 had significantly improved LRFS compared with those with MTR <0.2 (log-rank P = .0026) and reduced recurrence (subdistribution hazard ratio, 0.203; 95% CI, 0.067-0.619; P = .005). In multivariable Cox regression, MTR ≥0.2 remained an independent predictor of improved LRFS (hazard ratio, 0.15; 95% CI, 0.04-0.51; P = .003). For sublobar resection of invasive lung adenocarcinoma as mixed GGNs, a margin distance of >0.2 times the tumor diameter is clinically significant to optimize local control.

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