| Summary: | Background: An elevated level of low-density lipoprotein cholesterol (LDL-C) constitutes one of the most important modifiable risk factors for cardiovascular disease (CVD). Individuals with heterozygous familial hypercholesterolaemia (HeFH) are particularly vulnerable to CVD events. The addition of evolocumab to statins has shown marked reductions in LDL-C levels. The objective of this analysis is to demonstrate the clinical and economic value of LDL-C lowering with evolocumab from the Bulgarian public health care perspective. Methods: A disease-specific measure of health benefit was devised: Effectively treated patient-years (ETPYs) combine length of life with the likelihood of attaining best-practice recommendations on LDL-C lowering. “Effective treatment” was defined as a reduction in LDL-C levels of ≥50%. A Markov cohort state-transition model was adapted, considering a life-long treatment duration. Demographics, baseline characteristics and efficacy data were taken from the RUTHERFORD-2 trial. The model uses the relationship between LDL-C lowering and reduced CVD event rates observed in the meta-analyses conducted by the Cholesterol Treatment Trialists’ Collaboration. Outcomes and costs (from year 2015) were discounted at an annual rate of 5%. Sensitivity analyses were conducted to assess uncertainty surrounding the results. Results: The total incremental costs of evolocumab added to statins versus statins alone are BGN 120,329 while adding 9.30 ETPYs over lifetime. These results imply an incremental cost per ETPY of BGN 12,937 (US$ 7,215; € 6,604). The use of evolocumab is associated with a relative reduction in the CVD event rate by 38% (18% per 1 mmol/L). Conclusions: Adding evolocumab to statins may be considered cost-effective in light of an additional expense per patient-year gained in which individuals with HeFH receive effective treatment under the terms of international prevention guidelines. ETPYs are an intuitive and clinically meaningful measure of patient benefit that, in relation to costs, can support health care decision-making that considers quality of care.
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