Related Experiment Video
Updated: Nov 20, 2025

Multidimensional Coculture System to Model Lung Squamous Carcinoma Progression
Published on: March 17, 2020
Lepidic component identifies a subgroup of lung adenocarcinoma with a distinctive prognosis: a multicenter
Erjia Zhu1, Chenyang Dai1, Huikang Xie2
1Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, People's Republic of China.
Background:
Our aim was to investigate the prognostic impact of the lepidic component on T stage in patients with lung adenocarcinoma (LUAD).
Methods:
A retrospective data set including 863 cases of LUAD with lepidic component and 856 cases without lepidic component was used to identify matched lepidic-positive and lepidic-negative cohorts (n = 376 patients per group) using a propensity-score matching. Primary outcome variables included recurrence-free survival (RFS) and overall survival (OS). Prognostic factors were assessed by Cox regression analysis and Kaplan-Meier estimates.
Results:
Multivariate analysis revealed that lepidic component presence was an independent prognostic factor for prolonged RFS (p < 0.001) and OS (p < 0.001). Furthermore, lepidic ratio (LR) >25% or ⩽25% were confirmed to be independent prolonged survival predictors. No survival differences were observed between patients with LUAD with LR >25% or ⩽25% (RFS p = 0.333; OS p = 0.078). The 5-year OS rates of patients with LUAD with a lepidic component were 90% regardless of the T stage, and these survival rates were significantly better than those of patients with LUAD without a lepidic component in the corresponding T stage. Multivariate analysis confirmed that T stage was associated with survival only in patients with LUAD without a lepidic component.
Conclusions:
Lepidic component presence identifies a LUAD subgroup with an excellent prognosis independent of the LR, pathological T classification. Considering the lepidic component presence may improve prognostic predictions for patients with LUAD.
More Related Videos
07:43Using 22C3 Anti-PD-L1 Antibody Concentrate on Biopsy and Cytology Samples from Non-small Cell Lung Cancer Patients
Published on: September 25, 2018
06:51Utilizing 18F-FDG PET/CT Imaging and Quantitative Histology to Measure Dynamic Changes in the Glucose Metabolism in Mouse Models of Lung Cancer
Published on: July 21, 2018