Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Room E6153, Baltimore, MD 21205, USA.
BMC Med Res Methodol. 2012 Nov 19;12:173. doi: 10.1186/1471-2288-12-173.
Several quantitative approaches for benefit-harm assessment of health care interventions exist but it is unclear how the approaches differ. Our aim was to review existing quantitative approaches for benefit-harm assessment and to develop an organizing framework that clarifies differences and aids selection of quantitative approaches for a particular benefit-harm assessment.
We performed a review of the literature to identify quantitative approaches for benefit-harm assessment. Our team, consisting of clinicians, epidemiologists, and statisticians, discussed the approaches and identified their key characteristics. We developed a framework that helps investigators select quantitative approaches for benefit-harm assessment that are appropriate for a particular decisionmaking context.
Our framework for selecting quantitative approaches requires a concise definition of the treatment comparison and population of interest, identification of key benefit and harm outcomes, and determination of the need for a measure that puts all outcomes on a single scale (which we call a benefit and harm comparison metric). We identified 16 quantitative approaches for benefit-harm assessment. These approaches can be categorized into those that consider single or multiple key benefit and harm outcomes, and those that use a benefit-harm comparison metric or not. Most approaches use aggregate data and can be used in the context of single studies or systematic reviews. Although the majority of approaches provides a benefit and harm comparison metric, only four approaches provide measures of uncertainty around the benefit and harm comparison metric (such as a 95 percent confidence interval). None of the approaches considers the actual joint distribution of benefit and harm outcomes, but one approach considers competing risks when calculating profile-specific event rates. Nine approaches explicitly allow incorporating patient preferences.
The choice of quantitative approaches depends on the specific question and goal of the benefit-harm assessment as well as on the nature and availability of data. In some situations, investigators may identify only one appropriate approach. In situations where the question and available data justify more than one approach, investigators may want to use multiple approaches and compare the consistency of results. When more evidence on relative advantages of approaches accumulates from such comparisons, it will be possible to make more specific recommendations on the choice of approaches.
现已有多种定量方法可用于评估医疗干预措施的获益-风险,但这些方法之间的差异尚不明确。本研究旨在综述现有的获益-风险定量评估方法,并构建一个组织框架,以明确不同方法之间的差异,并有助于针对特定的获益-风险评估选择定量方法。
我们对文献进行了综述,以确定获益-风险评估的定量方法。我们的团队由临床医生、流行病学家和统计学家组成,对这些方法进行了讨论,并确定了它们的关键特征。我们构建了一个框架,帮助研究人员选择适合特定决策背景的获益-风险评估定量方法。
我们选择定量方法的框架需要对治疗比较和感兴趣的人群进行简明定义,确定关键获益和危害结局,并确定是否需要使用一种将所有结局置于单一尺度上的度量(我们称之为获益和危害比较度量)。我们确定了 16 种获益-风险评估的定量方法。这些方法可分为考虑单一或多种关键获益和危害结局的方法,以及使用或不使用获益-危害比较度量的方法。大多数方法使用汇总数据,可用于单项研究或系统综述的背景下。虽然大多数方法提供了获益和危害比较度量,但只有 4 种方法提供了获益和危害比较度量的不确定性度量(如 95%置信区间)。没有一种方法考虑获益和危害结局的实际联合分布,但有一种方法在计算特定特征的事件发生率时考虑了竞争风险。9 种方法明确允许纳入患者偏好。
定量方法的选择取决于获益-风险评估的具体问题和目标,以及数据的性质和可用性。在某些情况下,研究人员可能只能确定一种合适的方法。在问题和可用数据支持多种方法的情况下,研究人员可能希望使用多种方法,并比较结果的一致性。当通过这些比较积累了更多关于方法相对优势的证据时,就有可能对方法的选择提出更具体的建议。