A Model Using Support Vector Machines Recursive Feature Elimination (SVM-RFE) Algorithm to Classify Whether COPD Patients Have Been Continuously Managed According to GOLD Guidelines

• Main Authors: Xia J, Sun L, Xu S, Xiang Q, Zhao J, Xiong W, Xu Y, Chu S
• Format: Article
• Language: English
• Published: Dove Medical Press 2020-11-01
• Series: International Journal of COPD
• Subjects: copd; gold; continuous management; support vector machine
• Online Access: https://www.dovepress.com/a-model-using-support-vector-machines-recursive-feature-elimination-sv-peer-reviewed-article-COPD

Jie Xia,1– 4,* Lina Sun,5,* Suqin Xu,1– 4 Qiu Xiang,1– 4 Jianping Zhao,1– 4 Weining Xiong,1– 4 Yongjian Xu,1– 4 Shuyuan Chu1– 4,6 1Department of Respiratory and Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Sciences & Technology, Wuhan, People’s Republic of China; 2Wuhan Clinical Medical Research Center for Chronic Airway Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Sciences & Technology, Wuhan, People’s Republic of China; 3Key Laboratory of Pulmonary Diseases of Health Ministry, Tongji Hospital, Tongji Medical College, Huazhong University of Sciences & Technology, Wuhan, People’s Republic of China; 4Key Site of National Clinical Research Center for Respiratory Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Sciences & Technology, Wuhan, People’s Republic of China; 5Department of Respiratory and Critical Care Medicine, Peking University Third Hospital, Beijing, People’s Republic of China; 6Laboratory of Respiratory Disease, Affiliated Hospital of Guilin Medical University, Guilin, People’s Republic of China*These authors contributed equally to this workCorrespondence: Shuyuan Chu; Jie XiaDepartment of Respiratory and Critical Care Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Sciences & Technology, Wuhan, People’s Republic of ChinaTel [phone]; [phone]Email [e-mail]; [e-mail]: Patients with chronic obstructive pulmonary disease (COPD) would have a poor prognosis if they were not continuously managed according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines. We aim to develop a model to classify whether COPD patients have been continuously managed according to GOLD in the previous year.Methods: The Managed group were COPD patients from a prospective cohort from November 2017 to November 2019, who have been continuously managed according to GOLD for 1 year. The Control group were COPD patients who were not continuously managed according to GOLD. They were from a retrospective cohort from October 2016 to October 2017 in the same hospitals as the Managed group. A synthetic minority over-sampling technique (SMOTE) algorithm was used to up-sample the Managed group in a training dataset. Features for classification were selected using a support vector machine recursive feature elimination (SVM-RFE) algorithm. The classification model was developed using LibSVM, and its performance was assessed on the testing dataset.Results: The final analysis included 15 subjects in the Managed group and 191 in the Control group. SVM-RFE selects nine features including smoking history, post-bronchodilator (post-)FVC before management, and those after 1-year follow-up (BMI, moderate and severe AECOPD frequency in previous 12 months, mMRC score, post-FEV1, post-FEV1%pred, post-FVC, and post-FEV1/FVC). For our model, positive predictive value is 66.7%, F1 score is 0.978, and AUC is 0.987.Conclusion: SVM classifier combined with SVM-REF feature selection algorithm could achieve good classification between COPD patients who are or are not continuously managed. This model could be applied in clinical practice to help doctors make decisions and enhance COPD patients’ compliance with standard treatment.Keywords: COPD, GOLD, continuous management, support vector machine