Hornberger J
Department of Health Research and Policy, Department of Medicine, Stanford University School of Medicine, CA, USA.
Am J Public Health. 1998 Jan;88(1):61-7. doi: 10.2105/ajph.88.1.61.
This study illustrates a cost-benefit analysis of clinical trial design, using as an example a trial of folate supplementation to prevent cardiovascular disease.
Bayesian statistical and decision-analytic techniques were used to estimate the cost-benefit and sample size of a placebo-controlled trial of folate targeted to US citizens, aged 35 to 84 years, with elevated serum homocysteine levels. The main end point is event-free survival (i.e., survival without new ischemic heart disease or stroke) at 5 years.
Because the screening cost and annual cost and inconvenience of taking folate is small compared with the consequences of stroke, ischemic heart disease, or death, the increase in 5-year event-free survival with folate that should compel the use of folate is just 1.1%. The sample size per group needed to establish this level of folate's medical effectiveness is estimated to be 17310. Such a trial would provide an expected societal cost-benefit savings exceeding $11 billion within 15 years.
This study illustrates how Bayesian methods may help in assessing the societal cost-benefit consequences of proposed disease prevention trials, deciding which trials are worth sponsoring, and designing cost-effective trials.
本研究以一项叶酸补充剂预防心血管疾病的试验为例,阐述了临床试验设计的成本效益分析。
采用贝叶斯统计和决策分析技术,对一项针对美国35至84岁血清同型半胱氨酸水平升高的公民进行的叶酸安慰剂对照试验的成本效益和样本量进行估计。主要终点是5年时无事件生存(即无新发缺血性心脏病或中风的生存)。
由于与中风、缺血性心脏病或死亡的后果相比,叶酸的筛查成本、年度成本和服用不便程度较小,叶酸使5年无事件生存率提高从而促使使用叶酸的幅度仅为1.1%。估计要确定叶酸达到这一医疗有效性水平每组所需的样本量为17310。这样一项试验将在15年内为社会节省超过110亿美元的成本效益。
本研究说明了贝叶斯方法如何有助于评估拟议的疾病预防试验的社会成本效益后果,决定哪些试验值得资助,并设计具有成本效益的试验。