MOX-Modelling and Scientific Computing Laboratory, Department of Mathematics, Politecnico di Milano, Milano, Italy; Biostatistics Unit, Department of Medical Sciences, University of Trieste, Trieste, Italy; Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
Department of Statistics and Quantitative Methods, Unit of Biostatistics, Epidemiology and Public Health, University of Milano-Bicocca, Milan, Italy; National Centre for Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy.
Value Health. 2024 Jul;27(7):897-906. doi: 10.1016/j.jval.2024.03.008. Epub 2024 Mar 26.
This study aims to show the application of flexible statistical methods in real-world cost-effectiveness analyses applied in the cardiovascular field, focusing specifically on the use of proprotein convertase subtilisin-kexin type 9 inhibitors for hyperlipidemia.
The proposed method allowed us to use an electronic health database to emulate a target trial for cost-effectiveness analysis using multistate modeling and microsimulation. We formally established the study design and provided precise definitions of the causal measures of interest while also outlining the assumptions necessary for accurately estimating these measures using the available data. Additionally, we thoroughly considered goodness-of-fit assessments and sensitivity analyses of the decision model, which are crucial to capture the complexity of individuals' healthcare pathway and to enhance the validity of this type of health economic models.
In the disease model, the Markov assumption was found to be inadequate, and a "time-reset" timescale was implemented together with the use of a time-dependent variable to incorporate past hospitalization history. Furthermore, the microsimulation decision model demonstrated a satisfying goodness of fit, as evidenced by the consistent results obtained in the short-term horizon compared with a nonmodel-based approach. Notably, proprotein convertase subtilisin-kexin type 9 inhibitors revealed their favorable cost-effectiveness only in the long-term follow-up, with a minimum willingness to pay of 39 000 Euro/life years gained.
The approach demonstrated its significant utility in several ways. Unlike nonmodel-based or alternative model-based methods, it enabled to (1) investigate long-term cost-effectiveness comprehensively, (2) use an appropriate disease model that aligns with the specific problem under study, and (3) conduct subgroup-specific cost-effectiveness analyses to gain more targeted insights.
本研究旨在展示灵活的统计方法在心血管领域真实世界成本效益分析中的应用，特别是在用于治疗血脂异常的脯氨酰肽链内切酶枯草溶菌素 9 抑制剂方面。
本研究采用电子健康数据库，通过多状态建模和微观模拟来模拟目标试验进行成本效益分析。我们正式建立了研究设计，并对感兴趣的因果措施进行了精确定义，同时还概述了使用现有数据准确估计这些措施所需的假设。此外，我们还彻底考虑了决策模型的拟合优度评估和敏感性分析，这对于捕捉个体医疗路径的复杂性和提高此类健康经济模型的有效性至关重要。
在疾病模型中，我们发现马尔可夫假设不充分，因此采用了“时间重置”时间尺度，并使用时间相关变量来纳入过去的住院史。此外，微观模拟决策模型的拟合优度令人满意，与非模型基础方法相比，短期预测结果一致。值得注意的是，只有在长期随访中，脯氨酰肽链内切酶枯草溶菌素 9 抑制剂才显示出有利的成本效益，最低支付意愿为 39000 欧元/生命年。
该方法通过多种方式展示了其重要的实用性。与非模型基础或替代模型基础方法不同，它能够（1）全面研究长期成本效益，（2）使用与研究问题相匹配的适当疾病模型，以及（3）进行亚组特定的成本效益分析，以获得更有针对性的见解。
