Classification of familial hypercholesterolaemia using ordinal logistic regression

Chua Yung-An, . and Yap Bee Wah, . and Marshima Mohd Rosli, . and Muhammad Hamizan Jamaludin, . and Hapizah Mohd Nawawi, . and Muthukkaruppan Annamalai, . Classification of familial hypercholesterolaemia using ordinal logistic regression. pp. 1163-1177. ISSN 2231-8526

Familial hypercholesterolaemia (FH) is a genetic disease that causes the elevation of lowdensity lipoprotein cholesterol (LDL-C) which subsequently leads to premature coronary heart disease (CHD). Features which have been reported to be associated with FH include lipids level tendon xanthomata and history of CHD. The Ordinal Logistic Regression model using the classification of FH patients with the Dutch Lipid Clinic Network Criteria (DLCN) as the dependent variable (where 1Possible 2Probable 3Definite) was developed and evaluated for different types of link functions. The FH patients (n 449) were recruited from health screening programmes conducted in hospitals and clinics in Malaysia from 2010 to 2018. Results indicate there is a significant association between FH categories with demographic factors (ethnicity and smoking) and physical symptoms (corneal arcus and xanthomata). The Ordinal Logistic Regression using Cauchit link function has lower Akaike Information Criterion (AIC) value higher Nagelkerkes R-Square and classification accuracy compared to Probit and Logit link function diastolic blood pressure corneal arcus and xanthomata were found to be significant covariates of FH.

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Abstract

Familial hypercholesterolaemia (FH) is a genetic disease that causes the elevation of lowdensity lipoprotein cholesterol (LDL-C) which subsequently leads to premature coronary heart disease (CHD). Features which have been reported to be associated with FH include lipids level tendon xanthomata and history of CHD. The Ordinal Logistic Regression model using the classification of FH patients with the Dutch Lipid Clinic Network Criteria (DLCN) as the dependent variable (where 1Possible 2Probable 3Definite) was developed and evaluated for different types of link functions. The FH patients (n 449) were recruited from health screening programmes conducted in hospitals and clinics in Malaysia from 2010 to 2018. Results indicate there is a significant association between FH categories with demographic factors (ethnicity and smoking) and physical symptoms (corneal arcus and xanthomata). The Ordinal Logistic Regression using Cauchit link function has lower Akaike Information Criterion (AIC) value higher Nagelkerkes R-Square and classification accuracy compared to Probit and Logit link function diastolic blood pressure corneal arcus and xanthomata were found to be significant covariates of FH.

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Item Type:	Article
AGROVOC Term:	Hypercholesterolaemia
AGROVOC Term:	Genetic disorders
AGROVOC Term:	Coronary diseases
AGROVOC Term:	Classification
AGROVOC Term:	Regression analysis
AGROVOC Term:	patients
AGROVOC Term:	Ethnic groups
AGROVOC Term:	Blood pressure
AGROVOC Term:	Disease control
Depositing User:	Mr. AFANDI ABDUL MALEK
Last Modified:	24 Apr 2025 00:54
URI:	http://webagris.upm.edu.my/id/eprint/9354

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