Annemans Lieven, Brignone Mélanie, Druais Sylvain, De Pauw Ann, Gauthier Aline, Demyttenaere Koen
Ghent University Hospital, Block A, 2nd fl., De Pintelaan 185, 9000, Ghent, Belgium,
Pharmacoeconomics. 2014 May;32(5):479-93. doi: 10.1007/s40273-014-0138-x.
The objective of this study was to assess the cost effectiveness of commonly used antidepressants as first-line treatment of major depressive disorder (MDD) in Belgium.
The model structure was based on a decision tree developed by the Swedish TLV (Tandvårds- och läkemedelsförmånsverket) and adapted to the Belgium healthcare setting, using primary local data on the patterns of treatment and following KCE [Federal Knowledge Center (Federaal Kenniscentrum voor de Gezondheidszorg)] recommendations. Comparators were escitalopram, citalopram, fluoxetine, paroxetine, sertraline, duloxetine, venlafaxine, and mirtazapine. In the model, patients not achieving remission or relapsing after remission on the assessed treatment moved to a second therapeutic step (titration, switch, add-on, or transfer to a specialist). In case of failure in the second step or following a suicide attempt, patients were assumed to be referred to secondary care. The time horizon was 1 year and the analysis was conducted from the National Institute for Health and Disability Insurance (NIHDI; national health insurance) and societal perspectives. Remission rates were obtained from the TLV network meta-analysis and risk of relapse, efficacy following therapeutic change, risk of suicide attempts and related death, utilities, costs (2012), and resources were derived from the published literature and expert opinion. The effect of uncertainty in model parameters was estimated through scenario analyses and a probabilistic sensitivity analysis (PSA).
In the base-case analysis, escitalopram was identified as the optimal strategy: it dominated all other treatments except venlafaxine from the NIHDI perspective, against which it was cost effective with an incremental cost-effectiveness ratio of
Escitalopram was associated with the highest probability of being the optimal treatment from the NIHDI and societal perspectives. This analysis, based on new Belgian clinical practice data and following KCE requirements, provides additional information that may be used to guide the choice of treatments in the management of MDD in Belgium.
本研究的目的是评估比利时常用抗抑郁药作为重度抑郁症(MDD)一线治疗的成本效益。
模型结构基于瑞典TLV(瑞典卫生和药品福利局)开发的决策树,并根据比利时医疗保健环境进行了调整,使用了关于治疗模式的主要本地数据,并遵循KCE[联邦知识中心(联邦卫生保健知识中心)]的建议。对照药物为艾司西酞普兰、西酞普兰、氟西汀、帕罗西汀、舍曲林、度洛西汀、文拉法辛和米氮平。在模型中,接受评估治疗后未达到缓解或缓解后复发的患者进入第二个治疗步骤(滴定、换药、加用药物或转诊至专科医生)。如果第二步治疗失败或自杀未遂后,患者被假定转诊至二级护理。时间范围为1年,分析从国家健康与残疾保险研究所(NIHDI;国家健康保险)和社会角度进行。缓解率来自TLV网络荟萃分析,复发风险、治疗改变后的疗效、自杀未遂和相关死亡风险、效用、成本(2012年)以及资源来自已发表的文献和专家意见。通过情景分析和概率敏感性分析(PSA)估计模型参数不确定性的影响。
在基础案例分析中,艾司西酞普兰被确定为最佳策略:从NIHDI角度来看,除文拉法辛外,它优于所有其他治疗方法,与文拉法辛相比,其具有成本效益,增量成本效益比为每质量调整生命年(QALY)小于6352欧元。从社会角度来看,艾司西酞普兰也优于所有其他治疗方法。在每QALY 30000欧元的阈值下,从NIHDI角度来看,PSA显示艾司西酞普兰被确定为最佳策略的概率范围为61%(与文拉法辛相比)至100%(与氟西汀相比)。
从NIHDI和社会角度来看,艾司西酞普兰是最佳治疗方法的可能性最高。基于比利时新的临床实践数据并遵循KCE要求的这一分析提供了可用于指导比利时MDD管理中治疗选择的额外信息。