1. Establishment of discriminative models for predicting the infiltration degree of patients with lung adenocarcinoma based on clinical laboratory indicators
- Author
-
WANG Mengfei, YANG Shouzhi, QIAO Yongxia, and HUANG Lin
- Subjects
lung adenocarcinoma ,tumor markers ,coagulation function indicators ,clinical biochemical indicators ,predictive discriminative model ,Medicine - Abstract
Objective·To establish a multifactorial discriminative model for predicting the degree of infiltration in patients with non-small cell lung adenocarcinoma based on clinically accessible laboratory indicators, such as tumor markers, coagulation function indicators, routine blood count indicators, and biochemical indicators.Methods·A retrospective study was conducted on 202 patients with lung adenocarcinoma admitted to Shanghai Chest Hospital in 2022. Multifactorial Logistic regression analysis was applied to screen independent factors that influenced the predictive infiltration degree of lung adenocarcinoma and to establish a regression model. In addition, machine learning was used to construct a discriminative model, and the area under the receiver operating characteristic curve (AUC) was used to evaluate the discriminative ability of the model to discriminate the degree of infiltration in lung adenocarcinoma patients.Results·A total of 202 patients with lung adenocarcinoma were included in the study, and divided into pre-invasive lesion group (n=59) and invasive lesion group (n=143). Multifactorial Logistic regression analysis revealed that urea, percentage of basophilic granulocytes, and albumin were independent factors for predicting the degree of infiltration of lung adenocarcinoma (all P
- Published
- 2024
- Full Text
- View/download PDF