Heterozygous familial hypercholesterolemia (HeFH) is a prevalent, monogenetic disorder characterized by a lifelong two- to threefold elevation of plasma low-density lipoprotein cholesterol (LDL-C) and high risk of premature coronary artery disease (CAD)1. Since patients with HeFH exhibit signs of atherosclerosis at young age2,3, early and aggressive LDL-C lowering interventions are recommended by current clinical guidelines4. Statins are the preferred primary pharmacological therapy4.

Non-adherence to statin therapy is one of the main challenges that physicians are faced with4, as it is associated with an increased risk of CAD in both primary and secondary prevention settings5,6. Studies investigating statin adherence show a wide range of adherence rates. For example, in a meta-analysis of 12 studies (comprising data from almost 800,000 adults) on the association between statin adherence and mortality, adherence rates between 20% and 89% were reported7. A 10-year follow-up study in young adult HeFH patients showed that 79% were adherent8, and another study with HeFH patients up to 40 years reported a mean adherence of 69% in the first year of treatment9.

Although prevalence and predictors of statin adherence have been extensively documented in general primary prevention patients10, information on predictors of adherence for patients with HeFH is scarce. FH patients are generally younger, asymptomatic and without co-morbidities compared to the general primary prevention patient. Predicting adherence in these patients is of particular importance given the often early start, lifelong necessity and clear benefits of statin therapy in HeFH patients11,12. Since FH patients might visit the clinic very infrequently after optimal titration of statin therapy, structural and repetitive monitoring of patients at risk for non-adherence is an important aspect in the prevention of CAD. Better prediction of statin adherence could aid in planning timely interventions in patients at risk for non-adherence.

Therefore, the aim of this study was to develop a dynamic prediction model to estimate the probability of statin adherence for individual HeFH patients for each upcoming prescription.