目的:评估心血管疾病(CVD)的干预措施需要评估其效用。我们旨在1)系统地审查自2013年以来发布的CVD的效用估计,2)严格评估英国相关的估计并计算相应的基线效用乘数。
方法:我们使用CVD和效用项搜索了MEDLINE和Embase(2021年4月22日)。我们筛选了主要研究的结果,这些研究报告了有心力衰竭经历的人的效用分布,心肌梗塞,外周动脉疾病,稳定型心绞痛,中风,短暂性脑缺血发作,或者不稳定型心绞痛.我们从包括的研究中提取了特征。对于基于EuroQoL5维(EQ-5D)度量的英国估计,我们评估了偏差风险和对决策分析模型的适用性,适当的合并臂/时间点,并使用没有CVD的年龄和性别匹配人群的预测效用来估计基线效用乘数。我们从具有低偏倚风险的直接适用研究中寻求效用来源,在我们的基本案例模型中优先考虑严重性排序的合理性,并在敏感性分析中确定最高的人群。
结果:确定的403项研究大多数使用EQ-5D(n=217),评估最多的经济合作与发展组织(n=262)。虽然措施和国家差异很大。使用EQ-5D(n=29)的英国研究为每种类型的CVD产生了非常异质的基线效用乘数,排除荟萃分析并暗示不同的可能严重程度顺序。我们可以找到提供合理的公用事业订购的来源,同时充分代表健康状态。
结论:我们对国际CVD效用估计进行了分类,并计算了英国相关的基线效用乘数。建模人员应考虑未报告的异构源,比如人口差异,从评论中选择效用证据时。
结论:发表的系统综述总结了截至2013年发表的与心血管疾病相关的效用估计。我们1)回顾了自2013年以来发表的7种心血管疾病的效用估计,2)严格评估了英国相关研究,和3)估计每种心血管疾病对基线效用的影响。我们的综述1)为7种类型的心血管疾病推荐了一组一致且可靠的基线效用乘数,2)为寻求自身背景的效用证据的研究人员提供了系统识别的参考信息。
OBJECTIVE: Evaluating interventions for cardiovascular disease (CVD) requires estimates of its effect on utility. We aimed to 1) systematically
review utility estimates for CVDs published since 2013 and 2) critically appraise UK-relevant estimates and calculate corresponding baseline utility multipliers.
METHODS: We searched MEDLINE and Embase (April 22, 2021) using CVD and utility terms. We screened results for primary studies reporting utility distributions for people with experience of heart failure, myocardial infarction, peripheral arterial disease, stable angina, stroke, transient ischemic attack, or unstable angina. We extracted characteristics from studies included. For UK estimates based on the EuroQoL 5-dimension (EQ-5D) measure, we assessed risk of bias and applicability to a decision-analytic model, pooled arms/time points as appropriate, and estimated baseline utility multipliers using predicted utility for age- and sex- matched populations without CVD. We sought utility sources from directly applicable studies with low risk of bias, prioritizing plausibility of severity ordering in our base-case model and highest population ascertainment in a sensitivity analysis.
RESULTS: Most of the 403 studies identified used EQ-5D (n = 217) and most assessed Organisation for Economic Co-operation and Development populations (n = 262), although measures and countries varied widely. UK studies using EQ-5D (n = 29) produced very heterogeneous baseline utility multipliers for each type of CVD, precluding meta-analysis and implying different possible severity orderings. We could find sources that provided a plausible ordering of utilities while adequately representing health states.
CONCLUSIONS: We cataloged international CVD utility estimates and calculated UK-relevant baseline utility multipliers. Modelers should consider unreported sources of heterogeneity, such as population differences, when selecting utility evidence from reviews.
CONCLUSIONS: Published systematic reviews have summarized estimates of utility associated with cardiovascular disease published up to 2013.We 1) reviewed utility estimates for 7 types of cardiovascular disease published since 2013, 2) critically appraised UK-relevant studies, and 3) estimated the effect of each cardiovascular disease on baseline utility.Our
review 1) recommends a consistent and reliable set of baseline utility multipliers for 7 types of cardiovascular disease and 2) provides systematically identified reference information for researchers seeking utility evidence for their own context.