Classification of familial hypercholesterolaemia using ordinal logistic regression

Abstract

Familial hypercholesterolaemia (FH) is a genetic disease that causes the elevation of low- density 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 1=Possible, 2=Probable, 3=Definite) 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 Nagelkerke’s 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.