Preoperative prognostic prediction for stage I lung adenocarcinomas: Impact of the computed tomography features associated with the new histological grading system

Objectives This study aimed to identify the computed tomography (CT) features associated with the new International Association for the Study of Lung Cancer (IASLC) three-tiered grading system to improve the preoperative prediction of disease-free survival of stage I lung adenocarcinoma patients. Methods The study included 379 patients. Ordinal logistic regression analysis was used to identify the independent predictors of IASLC grades. The first multivariate Cox regression model (Model 1) was based on the significant factors from the univariate analysis. The second multivariate model (Model 2) excluded the histologic grade and based only on preoperative factors. Results Larger consolidation tumor ratio (OR=2.15, P <.001), whole tumor size (OR=1.74, P =.002), and higher CT value (OR=3.77, P =.001) were independent predictors of higher IASLC grade. Sixty patients experienced recurrences after 70.4 months of follow-up. Model 1 consisted of age (HR:1.05, P =.003), clinical T stage (HR:2.32, P <.001), histologic grade (HR:4.31, P <.001), and burrs sign (HR:5.96, P <.001). Model 2 consisted of age (HR,1.04; P =.015), clinical T stage (HR:2.49, P <.001), consolidation tumor ratio (HR:2.49, P =.016), whole tumor size (HR:2.81, P =.022), and the burrs sign (HR:4.55, P =.002). Model 1 had the best prognostic predictive performance, followed by Model 2, clinical T stage, and histologic grade. Conclusion CTR (cut-off values of <25% and ≥75%) and whole tumor size (cut-off value of 17 mm) could stratify patients into different prognosis and be used as preoperative surrogates for the IASLC grading system. Integrating these CT features with clinical T staging can improve the preoperative prognostic prediction for stage I lung adenocarcinoma patients.