CT-Pathology Size Discordance and Size-Threshold-Defined Potential Overtreatment in Early-Stage Lung Cancer: Restricted Cubic Spline Analysis, Decision Curve Analysis, and Bootstrap Validation in 1096 Patients.

[BACKGROUND] Current guidelines recommend lobectomy for tumors > 20 mm on CT, yet systematic CT-pathology size discordance may contribute to size-threshold-driven surgical decisions. We hypothesized that CT-based tumor diameter differs from pathological size near the 20 mm surgical boundary, potentially leading a proportion of patients to undergo more extensive resection than pathology would indicate under a size-only rule.

[METHODS] We retrospectively analyzed 1096 patients undergoing thoracoscopic surgery for clinical stage I non-small cell lung cancer at a single center (2020-2024). CT-pathology agreement was assessed via Bland-Altman analysis. Optimal CT cut-off was identified using restricted cubic spline (RCS) modeling, internally validated with bootstrap resampling (B = 2000), and evaluated by decision curve analysis (DCA).

[RESULTS] CT showed size-dependent bias: overestimation in small tumors (T1a: +4.21 mm) transitioning to underestimation in larger lesions (≥T2: -7.49 mm). At the 20 mm threshold, 15.8% of patients (n = 173) underwent lobectomy despite pathological size ≤ 20 mm (potential overtreatment). RCS modeling and bootstrap-optimized DCA identified 23 mm as the candidate revised threshold. Adopting CT > 23 mm would reclassify 108 patients from lobectomy to sublobar resection, reducing size-threshold-defined potential overtreatment by 51.4% while maintaining sensitivity for true ≥ T2 tumors.

[CONCLUSIONS] CT demonstrates size-dependent discordance with pathological size; this discordance likely reflects both CT measurement inaccuracy and specimen shrinkage after fixation, and the relative contributions cannot be separated from these data. A candidate 23 mm CT threshold, supported by DCA and internal bootstrap validation, could reduce size-threshold-defined potential overtreatment by 51% in this cohort. Prospective multicenter validation is required before clinical implementation.