TY - JOUR
T1 - A LASSO-Derived Risk Model for Subclinical CAC Progression in Asian Population With an Initial Score of Zero
AU - Wu, Yun Ju
AU - Mar, Guang Yuan
AU - Wu, Ming Ting
AU - Wu, Fu Zong
N1 - Publisher Copyright:
Copyright © 2021 Wu, Mar, Wu and Wu.
PY - 2021/1/15
Y1 - 2021/1/15
N2 - 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.
AB - 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.
KW - CAC progression
KW - nomogram
KW - prediction model
KW - subclinical atherosclerosis
KW - zero score
UR - http://www.scopus.com/inward/record.url?scp=85106155387&partnerID=8YFLogxK
U2 - 10.3389/fcvm.2020.619798
DO - 10.3389/fcvm.2020.619798
M3 - Article
AN - SCOPUS:85106155387
SN - 2297-055X
VL - 7
JO - Frontiers in Cardiovascular Medicine
JF - Frontiers in Cardiovascular Medicine
M1 - 619798
ER -