Allore Heather, McAvay Gail, Vaz Fragoso Carlos A, Murphy Terrence E
Department of Medicine, Yale School of Medicine, New Haven, Connecticut, USA; Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USA.
Department of Medicine, Yale School of Medicine, New Haven, Connecticut, USA.
Int J Stat Med Res. 2016;5(1):48-55. doi: 10.6000/1929-6029.2016.05.01.5.
Approximately 75% of adults over the age of 65 years are affected by two or more chronic medical conditions. We provide a conceptual justification for individualized absolute risk calculators for competing patient-centered outcomes (PCO) (i.e. outcomes deemed important by patients) and patient reported outcomes (PRO) (i.e. outcomes patients report instead of physiologic test results). The absolute risk of an outcome is the probability that a person receiving a given treatment will experience that outcome within a pre-defined interval of time, during which they are simultaneously at risk for other competing outcomes. This allows for determination of the likelihood of a given outcome with and without a treatment. We posit that there are heterogeneity of treatment effects among patients with multiple chronic conditions (MCC) largely depends on those coexisting conditions. We outline the development of an individualized absolute risk calculator for competing outcomes using propensity score methods that strengthen causal inference for specific treatments. Innovations include the key concept that any given outcome may or may not concur with any other outcome and that these competing outcomes do not necessarily preclude other outcomes. Patient characteristics and MCC will be the primary explanatory factors used in estimating the heterogeneity of treatment effects on PCO and PRO. This innovative method may have wide-spread application for determining individualized absolute risk calculations for competing outcomes. Knowing the probabilities of outcomes in absolute terms may help the burgeoning population of patients with MCC who face complex treatment decisions.
65岁以上的成年人中,约75%受到两种或更多慢性疾病的影响。我们为针对以患者为中心的竞争性结局(PCO)(即患者认为重要的结局)和患者报告结局(PRO)(即患者报告的结局而非生理测试结果)的个体化绝对风险计算器提供了概念依据。结局的绝对风险是指接受特定治疗的人在预先定义的时间间隔内经历该结局的概率,在此期间他们同时面临其他竞争性结局的风险。这有助于确定接受治疗和不接受治疗时给定结局的可能性。我们认为,患有多种慢性病(MCC)的患者之间治疗效果存在异质性,这在很大程度上取决于那些共存的疾病。我们概述了使用倾向评分方法开发针对竞争性结局的个体化绝对风险计算器,该方法加强了对特定治疗的因果推断。创新之处包括关键概念,即任何给定结局可能与任何其他结局一致,也可能不一致,并且这些竞争性结局不一定排除其他结局。患者特征和MCC将是用于估计治疗效果对PCO和PRO异质性的主要解释因素。这种创新方法可能在确定竞争性结局的个体化绝对风险计算方面有广泛应用。从绝对角度了解结局的概率可能有助于面临复杂治疗决策的MCC患者群体不断增加。