Najafzadeh Mehdi, Schneeweiss Sebastian, Choudhry Niteesh, Bykov Katsiaryna, Kahler Kristijan H, Martin Diane P, Gagne Joshua J
Department of Medicine, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Department of Medicine, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
Value Health. 2015 Mar;18(2):250-9. doi: 10.1016/j.jval.2014.11.001. Epub 2015 Feb 2.
Patients, physicians, and other decision makers make implicit but inevitable trade-offs among risks and benefits of treatments. Many methods have been proposed to promote transparent and rigorous benefit-risk analysis (BRA).
To propose a framework for classifying BRA methods on the basis of key factors that matter most for patients by using a common mathematical notation and compare their results using a hypothetical example.
We classified the available BRA methods into three categories: 1) unweighted metrics, which use only probabilities of benefits and risks; 2) metrics that incorporate preference weights and that account for the impact and duration of benefits and risks; and 3) metrics that incorporate weights based on decision makers' opinions. We used two hypothetical antiplatelet drugs (a and b) to compare the BRA methods within our proposed framework.
Unweighted metrics include the number needed to treat and the number needed to harm. Metrics that incorporate preference weights include those that use maximum acceptable risk, those that use relative-value-adjusted life-years, and those that use quality-adjusted life-years. Metrics that use decision makers' weights include the multicriteria decision analysis, the benefit-less-risk analysis, Boers' 3 by 3 table, the Gail/NCI method, and the transparent uniform risk benefit overview. Most BRA methods can be derived as a special case of a generalized formula in which some are mathematically identical. Numerical comparison of methods highlights potential differences in BRA results and their interpretation.
The proposed framework provides a unified, patient-centered approach to BRA methods classification based on the types of weights that are used across existing methods, a key differentiating feature.
患者、医生和其他决策者在治疗的风险和益处之间进行着隐含但不可避免的权衡。已经提出了许多方法来促进透明且严谨的效益-风险分析(BRA)。
通过使用通用数学符号,基于对患者最重要的关键因素,提出一种对BRA方法进行分类的框架,并使用一个假设示例比较它们的结果。
我们将现有的BRA方法分为三类:1)未加权指标,仅使用益处和风险的概率;2)纳入偏好权重并考虑益处和风险的影响及持续时间的指标;3)基于决策者意见纳入权重的指标。我们使用两种假设的抗血小板药物(a和b)在我们提出的框架内比较BRA方法。
未加权指标包括治疗所需人数和伤害所需人数。纳入偏好权重的指标包括使用最大可接受风险的指标、使用相对价值调整生命年的指标以及使用质量调整生命年的指标。使用决策者权重的指标包括多标准决策分析、效益-低风险分析、布尔3× 3表格、盖尔/美国国立癌症研究所方法以及透明统一风险效益概述。大多数BRA方法可以作为一个通用公式的特殊情况推导出来,其中一些在数学上是相同的。方法的数值比较突出了BRA结果及其解释方面的潜在差异。
所提出的框架基于现有方法中使用的权重类型,提供了一种统一的、以患者为中心的BRA方法分类方法,这是一个关键的区别特征。