Lee Sang-Jun, Yoon Sung-Soo, Lee Myeong-Hoon, Kim Hye-Jun, Lim Yohwan, Park Hyewon, Park Sun Jae, Jeong Seogsong, Han Hyun-Wook
Department of Biomedical Informatics, School of Medicine, CHA University, Seongnam 13488, Korea.
Institute of Basic Medical Sciences, School of Medicine, CHA University, Seongnam 13488, Korea.
J Clin Med. 2022 Jun 2;11(11):3181. doi: 10.3390/jcm11113181.
Chronic obstructive pulmonary disease (COPD) is considered a major cause of death worldwide, and various studies have been conducted for its early diagnosis. Our work developed a scoring system by predicting and validating COPD and performed predictive model implementations. Participants who underwent a health screening between 2017 and 2020 were extracted from the Korea National Health and Nutrition Examination Survey (KNHANES) database. COPD individuals were defined as aged 40 years or older with prebronchodilator forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC < 0.7). The logistic regression model was performed, and the C-index was used for variable selection. Receiver operating characteristic (ROC) curves with area under the curve (AUC) values were generated for evaluation. Age, sex, waist circumference and diastolic blood pressure were used to predict COPD and to develop a COPD score based on a multivariable model. A simplified model for COPD was validated with an AUC value of 0.780 from the ROC curves. In addition, we evaluated the association of the derived score with cardiovascular disease (CVD). COPD scores showed significant performance in COPD prediction. The developed score also showed a good effect on the diagnostic ability for CVD risk. In the future, studies comparing the diagnostic accuracy of the derived scores with standard diagnostic tests are needed.
慢性阻塞性肺疾病(COPD)被认为是全球主要的死亡原因之一,并且已经针对其早期诊断开展了各种研究。我们的工作通过预测和验证COPD开发了一种评分系统,并进行了预测模型的实施。从韩国国家健康与营养检查调查(KNHANES)数据库中提取了2017年至2020年期间接受健康筛查的参与者。COPD个体被定义为年龄在40岁及以上、支气管扩张剂使用前1秒用力呼气量/用力肺活量(FEV1/FVC < 0.7)的人群。进行了逻辑回归模型分析,并使用C指数进行变量选择。生成了带有曲线下面积(AUC)值的受试者工作特征(ROC)曲线用于评估。使用年龄、性别、腰围和舒张压来预测COPD,并基于多变量模型开发COPD评分。通过ROC曲线验证了一个简化的COPD模型,其AUC值为0.780。此外,我们评估了所推导的评分与心血管疾病(CVD)之间的关联。COPD评分在COPD预测中表现出显著性能。所开发的评分在CVD风险诊断能力方面也显示出良好效果。未来,需要开展将所推导评分的诊断准确性与标准诊断测试进行比较的研究。