Cargando…

A LASSO-Derived Risk Model for Subclinical CAC Progression in Asian Population With an Initial Score of Zero

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:...

Descripción completa

Detalles Bibliográficos
Autores principales: Wu, Yun-Ju, Mar, Guang-Yuan, Wu, Ming-Ting, Wu, Fu-Zong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7843450/
https://www.ncbi.nlm.nih.gov/pubmed/33521068
http://dx.doi.org/10.3389/fcvm.2020.619798
_version_ 1783644146348589056
author Wu, Yun-Ju
Mar, Guang-Yuan
Wu, Ming-Ting
Wu, Fu-Zong
author_facet Wu, Yun-Ju
Mar, Guang-Yuan
Wu, Ming-Ting
Wu, Fu-Zong
author_sort Wu, Yun-Ju
collection PubMed
description 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.
format Online
Article
Text
id pubmed-7843450
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-78434502021-01-30 A LASSO-Derived Risk Model for Subclinical CAC Progression in Asian Population With an Initial Score of Zero Wu, Yun-Ju Mar, Guang-Yuan Wu, Ming-Ting Wu, Fu-Zong Front Cardiovasc Med Cardiovascular Medicine 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. Frontiers Media S.A. 2021-01-15 /pmc/articles/PMC7843450/ /pubmed/33521068 http://dx.doi.org/10.3389/fcvm.2020.619798 Text en Copyright © 2021 Wu, Mar, Wu and Wu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cardiovascular Medicine
Wu, Yun-Ju
Mar, Guang-Yuan
Wu, Ming-Ting
Wu, Fu-Zong
A LASSO-Derived Risk Model for Subclinical CAC Progression in Asian Population With an Initial Score of Zero
title A LASSO-Derived Risk Model for Subclinical CAC Progression in Asian Population With an Initial Score of Zero
title_full A LASSO-Derived Risk Model for Subclinical CAC Progression in Asian Population With an Initial Score of Zero
title_fullStr A LASSO-Derived Risk Model for Subclinical CAC Progression in Asian Population With an Initial Score of Zero
title_full_unstemmed A LASSO-Derived Risk Model for Subclinical CAC Progression in Asian Population With an Initial Score of Zero
title_short A LASSO-Derived Risk Model for Subclinical CAC Progression in Asian Population With an Initial Score of Zero
title_sort lasso-derived risk model for subclinical cac progression in asian population with an initial score of zero
topic Cardiovascular Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7843450/
https://www.ncbi.nlm.nih.gov/pubmed/33521068
http://dx.doi.org/10.3389/fcvm.2020.619798
work_keys_str_mv AT wuyunju alassoderivedriskmodelforsubclinicalcacprogressioninasianpopulationwithaninitialscoreofzero
AT marguangyuan alassoderivedriskmodelforsubclinicalcacprogressioninasianpopulationwithaninitialscoreofzero
AT wumingting alassoderivedriskmodelforsubclinicalcacprogressioninasianpopulationwithaninitialscoreofzero
AT wufuzong alassoderivedriskmodelforsubclinicalcacprogressioninasianpopulationwithaninitialscoreofzero
AT wuyunju lassoderivedriskmodelforsubclinicalcacprogressioninasianpopulationwithaninitialscoreofzero
AT marguangyuan lassoderivedriskmodelforsubclinicalcacprogressioninasianpopulationwithaninitialscoreofzero
AT wumingting lassoderivedriskmodelforsubclinicalcacprogressioninasianpopulationwithaninitialscoreofzero
AT wufuzong lassoderivedriskmodelforsubclinicalcacprogressioninasianpopulationwithaninitialscoreofzero