Brinkley Jason, Tsiatis Anastasios, Anstrom Kevin J
Department of Biostatistics, East Carolina University, Greenville, North Carolina 27834, USA.
Biometrics. 2010 Jun;66(2):512-22. doi: 10.1111/j.1541-0420.2009.01282.x. Epub 2009 Jun 9.
For many diseases where there are several treatment options often there is no consensus on the best treatment to give individual patients. In such cases, it may be necessary to define a strategy for treatment assignment; that is, an algorithm that dictates the treatment an individual should receive based on their measured characteristics. Such a strategy or algorithm is also referred to as a treatment regime. The optimal treatment regime is the strategy that would provide the most public health benefit by minimizing as many poor outcomes as possible. Using a measure that is a generalization of attributable risk (AR) and notions of potential outcomes, we derive an estimator for the proportion of events that could have been prevented had the optimal treatment regime been implemented. Traditional AR studies look at the added risk that can be attributed to exposure of some contaminant; here we will instead study the benefit that can be attributed to using the optimal treatment strategy. We will show how regression models can be used to estimate the optimal treatment strategy and the attributable benefit of that strategy. We also derive the large sample properties of this estimator. As a motivating example, we will apply our methods to an observational study of 3856 patients treated at the Duke University Medical Center with prior coronary artery bypass graft surgery and further heart-related problems requiring a catheterization. The patients may be treated with either medical therapy alone or a combination of medical therapy and percutaneous coronary intervention without a general consensus on which is the best treatment for individual patients.
对于许多存在多种治疗选择的疾病，对于给个体患者提供最佳治疗方法往往没有共识。在这种情况下，可能有必要定义一种治疗分配策略；也就是说，一种根据个体测量特征来决定其应接受何种治疗的算法。这样的策略或算法也被称为治疗方案。最优治疗方案是通过尽可能减少不良结局来提供最大公共卫生效益的策略。使用一种可归因风险（AR）的广义度量和潜在结果的概念，我们推导出一个估计值，用于估计如果实施最优治疗方案原本可以预防的事件比例。传统的AR研究关注可归因于某种污染物暴露的额外风险；在这里，我们将转而研究可归因于使用最优治疗策略的益处。我们将展示如何使用回归模型来估计最优治疗策略及其该策略的可归因益处。我们还推导出了这个估计值的大样本性质。作为一个激励性示例，我们将把我们的方法应用于一项对3856名在杜克大学医学中心接受过冠状动脉搭桥手术且因进一步的心脏相关问题需要进行导管插入术的患者的观察性研究。这些患者可以单独接受药物治疗，也可以接受药物治疗与经皮冠状动脉介入治疗的联合治疗，对于个体患者哪种是最佳治疗方法并没有普遍共识。
