Clinical Pharmacology Department, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria La Princesa (IIS-Princesa), Faculty of Medicine, Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain.
Clinical Pharmacology Department, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria La Princesa (IIS-Princesa), Faculty of Medicine, Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, 28029 Madrid, Spain.
J Affect Disord. 2024 Nov 15;365:597-605. doi: 10.1016/j.jad.2024.08.154. Epub 2024 Aug 24.
Major depressive disorder (MDD) represents a sizable economic burden in Spain. Pharmacogenetic (PGx) screening to guide the choice of antidepressant medication (ADM) in MDD patients yields higher response and remission rates, which could reduce both healthcare and indirect costs.
We built a cost-effectiveness probabilistic Markov model with microsimulation using Tree Age Pro 2022, simulating a patient cohort from the SNHS starting ADM for MDD, and comparing PGx screening before starting ADM versus no screening (No PGx). We carried out a probabilistic sensitivity analysis using the Monte Carlo simulation with microsimulation, set for 1000 iterations and 1000 microsimulation trials, both from societal and healthcare provider perspectives, for a time horizon of 3 years.
From a societal perspective, the model estimated a mean cost of 3172.85€ and effectiveness of 2.64 quality-adjusted life years (QALYs) for the No PGx strategy, and a mean cost of 1687.02€ and effectiveness of 2.84 QALYs for the PGx strategy. The mean ICER was -7820.56 €/QALY. From a healthcare provider perspective (no indirect costs considered), the mean cost was 662.62€ for the No PGx strategy, and 446.60€ for the PGx strategy. The mean ICER was -1130.16 €/QALY.
The heterogeneity of input data from the literature, the need for assumptions of homogeneous distribution of variables and events across population and time, and the inherent limitations of cost-effectiveness analysis should be considered. The model omits combined therapies (ADMs with mood stabilizers, antipsychotics, cognitive behavioral therapy…).
PGx screening in MDD prior to ADM start is a dominant strategy in the SNHS.
重度抑郁症（MDD）在西班牙造成了相当大的经济负担。对 MDD 患者进行药物遗传学（PGx）筛查以指导抗抑郁药物（ADM）的选择，可以提高反应率和缓解率，从而降低医疗保健和间接成本。
我们使用 TreeAge Pro 2022 构建了一个基于微观模拟的成本效益概率马尔可夫模型，模拟了来自 SNHS 的 MDD 患者开始 ADM 的患者队列，并比较了在开始 ADM 之前进行 PGx 筛查与不进行筛查（无 PGx）的情况。我们从社会和医疗保健提供者的角度，使用蒙特卡罗模拟和微观模拟进行了概率敏感性分析，模拟次数为 1000 次，微观模拟试验为 1000 次，时间范围为 3 年。
从社会角度来看，该模型估计无 PGx 策略的平均成本为 3172.85 欧元，有效性为 2.64 个质量调整生命年（QALY），PGx 策略的平均成本为 1687.02 欧元，有效性为 2.84 QALY。平均增量成本效益比（ICER）为-7820.56 欧元/QALY。从医疗保健提供者的角度来看（不考虑间接成本），无 PGx 策略的平均成本为 662.62 欧元，PGx 策略的平均成本为 446.60 欧元。平均 ICER 为-1130.16 欧元/QALY。
应考虑来自文献的输入数据的异质性、需要假设变量和事件在人群和时间上的均匀分布，以及成本效益分析的固有局限性。该模型忽略了联合治疗（ADM 与心境稳定剂、抗精神病药、认知行为疗法等）。
在 SNHS，ADM 开始前对 MDD 进行 PGx 筛查是一种优势策略。
