Health Outcome Effects of Common Medications in Elders with Multiple Conditions

描述(由申请人提供)：要为患有多种慢性病(MCC)的患者提供临床决策信息，我们必须比较不同条件下的治疗效果。在这项研究中，我们超越了针对单一条件特定结果的单一条件治疗的比较效益的问题，开始探索跨多个条件的治疗对对患者有意义且受所有健康条件影响的多个普遍健康结果(例如，功能、症状和生存)的比较有效性。探索多种普遍的结果很重要，因为治疗可能会以不同的方式影响结果，而患有MCC的老年人的健康结果优先顺序也不同。虽然复杂，但这条调查路线是对RFA-AG-13-003的反应，并且对患有MCC的老年人具有最大的相关性。该项目建立在最近的工作基础上，在这些工作中，我们：1)确定了一组普遍的健康结果；2)确定了几种常见情况对这些结果的影响；3)开发了一种方法，用于确定共存情况对死亡的贡献百分比；4)确定了最常见的一对竞争情况；以及5)确定了针对一种情况的治疗对潜在竞争情况的影响。在进行这项工作时，我们逐渐认识到方法学上的挑战，这有助于解释为什么这一领域的研究稀缺，尽管它具有临床重要性。拟议的方法建立在我们最近在采用纵向结果的联合建模和开发平均归属分数的纵向延伸方面的工作的基础上。使用创新的分析方法，具体目标是：1)评估针对一组常见和病态慢性病的9种最常用的指南推荐药物类别对5种普遍健康结果的影响；以及2)估计每种药物对每种普遍结果的贡献百分比。参与者将是大型、特征良好、具有全国代表性的联邦医疗保险当前受益人调查(MCBS)队列的成员，他们拥有9项研究条件中的2项。从临床的角度来看，这一系列研究最终将通过确定总体效益最好的药物，为MCC患者提供一种基于证据的多药联用方法。结果将通过引入新的方法，确定在MCC患者中进行比较的有前景的治疗方法，以及确定效果大小和功率估计来为未来的研究提供信息。由于MCBS代表了具有不同MCC组合的全国老年人口，结果将提供研究药物相对效果的人口水平估计。

DESCRIPTION (provided by applicant): To inform clinical decision-making for persons with multiple chronic conditions (MCC), we must compare the effects of treatments across conditions. In this study, we go beyond the question of comparative benefit of treatments for a single condition on single condition-specific outcomes to begin exploring the comparative effectiveness of treatments across multiple conditions on multiple universal health outcomes (e.g. function, symptoms, and survival) that are meaningful to patients and that are affected by all health conditions. Multiple universal outcomes are important to explore because treatments may affect outcomes differently and older adults with MCC vary in their health outcome priorities. While complex, this line of investigation is responsive to the RFA-AG-13-003 and of utmost relevance for older individuals with MCC. The project builds on recent work in which we have: 1) identified a set of universal health outcomes; 2) determined the effect of several common conditions on these outcomes; 3) developed a method for determining the % contribution to death of co-occurring conditions; 4) identified the most common pairs of competing conditions; and 5) determined the effects of treatment for one condition on a potentially competing condition. In conducting this work, we have come to appreciate the methodological challenges that help explain the dearth of research in this area despite its clinical importance. The proposed methodology builds on our recent work in adapting joint modeling of longitudinal outcomes and developing the longitudinal extension of the average attributable fraction. Using innovative analytical methods, the Specific Aims are to: 1) estimate the effect of the 9 most commonly used guideline recommended medication classes for a set of common and morbid chronic conditions on 5 universal health outcomes; and 2) estimate the percent contribution of each medication to each universal outcome. Participants will be members of the large, well-characterized, nationally representative Medicare Current Beneficiary Survey (MCBS) cohort who have e 2 of the 9 study conditions. From a clinical perspective, this line of investigation eventually will allow an evidence-based approach to polypharmacy for patients with MCC by identifying medications with the best overall benefits. Results will inform future studies by introducing new methods, identifying promising treatments to compare in persons with MCC, and determining effect size and power estimates. Because MCBS represents the national older population with variable combinations of MCC, results will provide a population-level estimate of the relative effects of the study medications.