Effectiveness of Inclisiran and Evolocumab in LDL-C Goal Attainment: A Hybrid Decision Tree-Markov Model Analysis
Author(s)
César Ferreira, MsC1, Severina Moreira1, Marta Afonso-Silva, MsC2.
1Market Access, Novartis, Porto Salvo, Portugal, 2Novartis Farma - Produtos Farmaceuticos S.A., Porto Salvo, Portugal.
1Market Access, Novartis, Porto Salvo, Portugal, 2Novartis Farma - Produtos Farmaceuticos S.A., Porto Salvo, Portugal.
OBJECTIVES: Health decision-making should consider the potential real-world impact of treatments on patient outcomes. The number needed to treat (NNT) provides an intuitive estimate of absolute intervention benefit despite its limitations. This study aims to estimate the NNT of inclisiran and evolocumab in achieving low-density lipoprotein cholesterol (LDL-C) target levels as defined by the 2019 ESC/EAS guidelines.
METHODS: A hybrid decision tree-Markov model was employed to simulate the proportion of responders over a 10-year time horizon. Transition probabilities were calculated based on the proportion of patients achieving LDL-C target levels and discontinuation rates were retrieved from real-world data. Observational data demonstrated that 71.6% of patients treated with inclisiran (450 patients with 11 months of follow-up) and 60.0% of patients treated with evolocumab (1951 patients with up to 30 months follow-up) achieve LDL-C goals. Discontinuation rates per year were 19.8% for inclisiran and 43.7% for evolocumab.
RESULTS: Based on these data, the estimated NNT of inclisiran was lower than the NNT of evolocumab, regardless of the year cut-off. In fact, at year 3, the NNT of evolocumab (5.26) was almost 2.5 times higher than the NNT of inclisiran (2.17). At year 5, NNT of inclisiran was calculated to be 3.38 whereas of evolocumab it was estimated to be 16.59.
CONCLUSIONS: Inclisiran demonstrated a lower NNT when compared with evolocumab for achieving LDL-C targets, with differences increasing over time. These results are primarily driven by higher treatment persistence, shedding light on the influence that it might have in determining the effectiveness of lipid-lowering therapies in real-world practice.
METHODS: A hybrid decision tree-Markov model was employed to simulate the proportion of responders over a 10-year time horizon. Transition probabilities were calculated based on the proportion of patients achieving LDL-C target levels and discontinuation rates were retrieved from real-world data. Observational data demonstrated that 71.6% of patients treated with inclisiran (450 patients with 11 months of follow-up) and 60.0% of patients treated with evolocumab (1951 patients with up to 30 months follow-up) achieve LDL-C goals. Discontinuation rates per year were 19.8% for inclisiran and 43.7% for evolocumab.
RESULTS: Based on these data, the estimated NNT of inclisiran was lower than the NNT of evolocumab, regardless of the year cut-off. In fact, at year 3, the NNT of evolocumab (5.26) was almost 2.5 times higher than the NNT of inclisiran (2.17). At year 5, NNT of inclisiran was calculated to be 3.38 whereas of evolocumab it was estimated to be 16.59.
CONCLUSIONS: Inclisiran demonstrated a lower NNT when compared with evolocumab for achieving LDL-C targets, with differences increasing over time. These results are primarily driven by higher treatment persistence, shedding light on the influence that it might have in determining the effectiveness of lipid-lowering therapies in real-world practice.
Conference/Value in Health Info
2025-11, ISPOR Europe 2025, Glasgow, Scotland
Value in Health, Volume 28, Issue S2
Code
CO85
Topic
Clinical Outcomes, Economic Evaluation
Topic Subcategory
Comparative Effectiveness or Efficacy
Disease
Cardiovascular Disorders (including MI, Stroke, Circulatory)