Abstract
BackgroundIn clinical practice, preoperative identification of mixed ground-glass opacity (mGGO) nodules with micropapillary component (MPC) to facilitate the implementation of individualized therapeutic strategies and avoid unnecessary surgery is increasingly importantObjectiveThis study aimed to build a predictive model based on clinical and radiological variables for the early identification of MPC in lung adenocarcinoma presenting as mGGO nodules.MethodsThe enrolled 741 lung adenocarcinoma patients were randomly divided into a training cohort and a validation cohort (3:1 ratio). The pathological specimens and preoperative images of malignant mGGO nodules from the study subjects were retrospectively reviewed. Furthermore, in the training cohort, selected clinical and radiological variables were utilized to construct a predictive model for MPC prediction.ResultsThe MPC was found in 228 (43.3%) patients in the training cohort and 72 (41.1%) patients in the validation cohort. Based on the predictive nomogram, the air bronchogram was defined as the most dominant independent risk factor for MPC of mGGO nodules, followed by the maximum computed tomography (CT) value ( > 200), adjacent to pleura, gender (male), and vacuolar sign. The nomogram demonstrated good discriminative ability with a C-index of 0.783 (95%[CI] 0.744-0.822) in the training cohort and a C-index of 0.799 (95%[CI] 0.732-0.866) in the validation cohort Additionally, by using the bootstrapping method, this predictive model calculated a corrected AUC of 0.774 (95% CI: 0.770-0.779) in the training cohort.ConclusionsThis study proposed a predictive model for preoperative identification of MPC in known lung adenocarcinomas presenting as mGGO nodules to facilitate individualized therapy. This nomogram model needs to be further externally validated by subsequent multicenter studies.