Drug Treatment of Hyperlipidemia in Chinese Patients: Focus on the Use of Simvastatin and Ezetimibe Alone and in Combination.
Sheng-Na HanWei-Hong YangJian-Jian YinHai-Long TaoLi-Rong ZhangPublished in: American journal of cardiovascular drugs : drugs, devices, and other interventions (2019)
Elevated serum low-density lipoprotein cholesterol (LDL-C) is a major risk factor for coronary heart disease (CHD). Many guidelines recommend LDL-C as a primary treatment target, and statins represent the cornerstone of treatment for lipid management. Recently revised guidelines recommend even more intense management of LDL-C, especially in patients at moderate and high risk. However, LDL-C levels in the Chinese population differ from those in Western populations, and the benefits and safety of the maximum allowable dose of statins have yet to be determined. Furthermore, in practice, many patients do not achieve the increasingly stringent LDL-C goals. Consequently, alternative approaches to lipid management are required. Combination therapy with ezetimibe and a statin, which have complementary mechanisms of action, is more effective than statin monotherapies, even at high doses. Several clinical studies have consistently shown that combination therapy with ezetimibe and simvastatin lowers LDL-C more potently than statin monotherapies. Moreover, the safety and tolerability profile of the combination therapy appears to be similar to that of low-dose statin monotherapies. This review discusses the role of simvastatin in combination with ezetimibe in controlling dyslipidemia in Chinese patients, particularly the efficacy and safety of combination therapy in light of recently published clinical data.
Keyphrases
- combination therapy
- low density lipoprotein
- cardiovascular disease
- low dose
- coronary artery disease
- healthcare
- end stage renal disease
- emergency department
- type diabetes
- newly diagnosed
- randomized controlled trial
- clinical practice
- metabolic syndrome
- adipose tissue
- systematic review
- open label
- prognostic factors
- deep learning
- insulin resistance