Construction of a model for assessing the malignant risk of patients with gastric disease based on conventional laboratory indi-cators
10.13602/j.cnki.jcls.2024.09.03
- VernacularTitle:基于常规检验学指标构建胃部疾病患者恶性风险评估模型
- Author:
Mengmeng WANG
1
;
Xiujing HAN
;
Shuyi WU
;
Jiaqing HU
Author Information
1. 广州医科大学附属第一医院检验科,广州 510120
- Keywords:
gastric cancer;
non-atrophic gastritis;
serological marker;
hemoglobin;
risk prediction;
nomogram
- From:
Chinese Journal of Clinical Laboratory Science
2024;42(9):653-658
- CountryChina
- Language:Chinese
-
Abstract:
Objective To construct a model for predicting the benign and malignant risk of the patients with gastric diseases using con-ventional laboratory indicators such as tumor markers,blood routine,and coagulation indicators,and validate its predictive value.Methods The medical records of patients with gastric diseases who visited the First Affiliated Hospital of Guangzhou Medical Univer-sity from January 2018 to January 2023 were analyzed retrospectively.According to the pathological results,the patients were divided into the gastric cancer(GC)group(n=134)and chronic non-atrophic gastritis(CNAG)group(n=298).Their routine test data such as serum and whole blood tests were collected.The statistical analysis was conducted using the R 4.2.3 software,and a model for pre-dicting the risk of GC was constructed and validated.Results A model for predicting the risk of GC was constructed successfully using the Logistic regression analysis,which included D-dimer,carcinoembryonic antigen(CEA),carbohydrate antigen 72-4(CA72-4)and hemoglobin(Hb).A visual nomogram was plotted as the final prediction model.The areas under the receiver operating characteristic(ROC)curve(AUCROC)of the model in the training and testing sets were 0.809(95%CI:0.754-0.864)and 0.808(95%CI:0.724-0.892),respectively.The sensitivity and specificity of the model were 58.5%and 93.3%,respectively,indicating that it had good pre-dictive ability.Conclusion The model for predicting the malignant risk of patients with gastric diseases constructed using routine tes-ting indicators has good accuracy and can effectively predict the risk of gastric disease transforming into gastric cancer.It helps to find early gastric cancer patients in clinical practice and take targeted prevention and intervention measures.
