Yun-Ju Wu1,2, Guang-Yuan Mar3, Ming-Ting Wu1,4, Fu-Zong Wu1,4,5. 1. Department of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan. 2. Department of Health Care Administration, Chang Jung Christian University, Tainan, Taiwan. 3. Physical Examination Center, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan. 4. Faculty of Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan. 5. Department of Medical Imaging and Radiology, Shu-Zen Junior College of Medicine and Management, Kaohsiung, Taiwan.
Abstract
Background: This study is aimed at developing a prediction nomogram for subclinical coronary atherosclerosis in an Asian population with baseline zero score, and to compare its discriminatory ability with Framingham risk score (FRS) and atherosclerotic cardiovascular disease (ASCVD) models. Methods: Clinical characteristics, physical examination, and laboratory profiles of 830 subjects were retrospectively reviewed. Subclinical coronary atherosclerosis in term of Coronary artery calcification (CAC) progression was the primary endpoint. A nomogram was established based on a least absolute shrinkage and selection operator (LASSO)-derived logistic model. The discrimination and calibration ability of this nomogram was evaluated by Hosmer-Lemeshow test and calibration curves in the training and validation cohort. Results: Of the 830 subjects with baseline zero score with the average follow-up period of 4.55 ± 2.42 year in the study, these subjects were randomly placed into the training set or validation set at a ratio of 2.8:1. These study results showed in the 612 subjects with baseline zero score, 145 (23.69%) subjects developed CAC progression in the training cohort (N = 612), while in the validation cohort (N = 218), 51 (23.39%) subjects developed CAC progression. This LASSO-derived nomogram included the following 10 predictors: "sex," age," "hypertension," "smoking habit," "Gamma-Glutamyl Transferase (GGT)," "C-reactive protein (CRP)," "high-density lipoprotein cholesterol (HDL-C)," "cholesterol," "waist circumference," and "follow-up period." Compared with the FRS and ASCVD models, this LASSO-derived nomogram had higher diagnostic performance and lower Akaike information criterion (AIC) and Bayesian information criterion (BIC) value. The discriminative ability, as determined by the area under receiver operating characteristic curve was 0.780 (95% confidence interval: 0.731-0.829) in the training cohort and 0.836 (95% confidence interval: 0.761-0.911) in the validation cohort. Moreover, satisfactory calibration was confirmed by Hosmer-Lemeshow test with P-values of 0.654 and 0.979 in the training cohort and validation cohort. Conclusions: This validated nomogram provided a useful predictive value for subclinical coronary atherosclerosis in subjects with baseline zero score, and could provide clinicians and patients with the primary preventive strategies timely in individual-based preventive cardiology.
Background: This study is aimed at developing a prediction nomogram for subclinical coronary atherosclerosis in an Asian population with baseline zero score, and to compare its discriminatory ability with Framingham risk score (FRS) and atherosclerotic cardiovascular disease (ASCVD) models. Methods: Clinical characteristics, physical examination, and laboratory profiles of 830 subjects were retrospectively reviewed. Subclinical coronary atherosclerosis in term of Coronary artery calcification (CAC) progression was the primary endpoint. A nomogram was established based on a least absolute shrinkage and selection operator (LASSO)-derived logistic model. The discrimination and calibration ability of this nomogram was evaluated by Hosmer-Lemeshow test and calibration curves in the training and validation cohort. Results: Of the 830 subjects with baseline zero score with the average follow-up period of 4.55 ± 2.42 year in the study, these subjects were randomly placed into the training set or validation set at a ratio of 2.8:1. These study results showed in the 612 subjects with baseline zero score, 145 (23.69%) subjects developed CAC progression in the training cohort (N = 612), while in the validation cohort (N = 218), 51 (23.39%) subjects developed CAC progression. This LASSO-derived nomogram included the following 10 predictors: "sex," age," "hypertension," "smoking habit," "Gamma-Glutamyl Transferase (GGT)," "C-reactive protein (CRP)," "high-density lipoprotein cholesterol (HDL-C)," "cholesterol," "waist circumference," and "follow-up period." Compared with the FRS and ASCVD models, this LASSO-derived nomogram had higher diagnostic performance and lower Akaike information criterion (AIC) and Bayesian information criterion (BIC) value. The discriminative ability, as determined by the area under receiver operating characteristic curve was 0.780 (95% confidence interval: 0.731-0.829) in the training cohort and 0.836 (95% confidence interval: 0.761-0.911) in the validation cohort. Moreover, satisfactory calibration was confirmed by Hosmer-Lemeshow test with P-values of 0.654 and 0.979 in the training cohort and validation cohort. Conclusions: This validated nomogram provided a useful predictive value for subclinical coronary atherosclerosis in subjects with baseline zero score, and could provide clinicians and patients with the primary preventive strategies timely in individual-based preventive cardiology.
Authors: Pedro Covas; Eison De Guzman; Ian Barrows; Andrew J Bradley; Brian G Choi; Joseph M Krepp; Jannet F Lewis; Richard Katz; Cynthia M Tracy; Robert K Zeman; James P Earls; Andrew D Choi Journal: Front Cardiovasc Med Date: 2022-03-21
Authors: Po-Yi Li; Ru-Yih Chen; Fu-Zong Wu; Guang-Yuan Mar; Ming-Ting Wu; Fu-Wei Wang Journal: Int J Environ Res Public Health Date: 2021-05-20 Impact factor: 3.390