Evinacumab for treatment of familial hypercholesterolemia.
Bruce A WardenP Barton DuellPublished in: Expert review of cardiovascular therapy (2021)
Introduction: Familial hypercholesterolemia (FH) is characterized by lifelong elevation of low-density lipoprotein cholesterol (LDL-C), early onset coronary atherosclerosis, and premature death. FH is underdiagnosed and undertreated, but requires aggressive LDL-C-lowering to prevent complications. Current treatment strategies such as lifestyle modification and numerous LDL-C-lowering medications are often insufficient to achieve lipid goals in FH.Areas covered: Angiopoietin-like 3 protein (ANGPTL3) is intricately involved in lipid metabolism. Loss-of-function mutations in ANGPTL3 are associated with panhypolipidemia and reduced coronary atherosclerosis. Evinacumab, a fully human monoclonal antibody, inhibits ANGPTL3 and reduces multiple lipoprotein fractions ~50%, including LDL-C. The use of evinacumab within the FH population is described as well as its regulatory journey to an approved therapeutic.Expert opinion: Evinacumab, with its capacity to lower multiple lipoprotein fractions, particularly LDL-C, independently of LDLR function has potential to revolutionize treatment for FH patients. Current FDA-approval is only for homozygous FH (HoFH), arguably the most impactful indication, but use in other lipid disorders is under investigation. The short-term tolerability of evinacumab is very good, with infrequent, mild, and transient adverse events; however, long-term safety data are needed. The high cost and requirement for intravenous administration may limit adoption of evinacumab, but dramatic LDL-C-lowering and need for new therapeutic options for HoFH will drive interest.
Keyphrases
- low density lipoprotein
- early onset
- monoclonal antibody
- cardiovascular disease
- coronary artery
- coronary artery disease
- late onset
- electronic health record
- fatty acid
- ejection fraction
- physical activity
- newly diagnosed
- clinical trial
- metabolic syndrome
- type diabetes
- machine learning
- big data
- public health
- heart failure
- transcription factor
- atrial fibrillation
- drug administration
- left ventricular
- double blind
- patient reported outcomes