Health Outcome Effects of Common Medications in Elders with Multiple Conditions

描述（由申请人提供）：为了告知患有多种慢性疾病（MCC）的人的临床决策，我们必须比较不同疾病的治疗效果。在这项研究中，我们超越了单一条件下治疗对单一条件特定结果的比较效益问题，开始探索多种条件下治疗对多种普遍健康结果（例如功能，症状和生存）的比较有效性，这些结果对患者有意义并且受所有健康状况的影响。探索多种普遍结果是很重要的，因为治疗可能会对结果产生不同的影响，而且老年MCC患者的健康结果优先级各不相同。虽然复杂，但这条调查路线对RFA-AG-13-003有反应，对老年MCC患者有最大的相关性。该项目以我们最近开展的工作为基础：1)确定了一套全民健康结果；2)确定几种常见情况对这些结果的影响；3)开发了一种方法来确定共同发生的疾病对死亡的贡献百分比；4)确定最常见的竞争条件对；5)确定一种疾病的治疗对潜在竞争疾病的影响。在进行这项工作时，我们已经认识到方法上的挑战，这些挑战有助于解释尽管该领域具有临床重要性，但该领域研究的缺乏。所提出的方法建立在我们最近在纵向结果的联合建模和发展平均归因分数的纵向扩展方面的工作。使用创新的分析方法，具体目标是：1)估计一组常见和病态慢性病的9种最常用指南推荐药物类别对5种普遍健康结局的影响；2)估计每种药物对每种普遍结果的贡献百分比。参与者将是具有9项研究条件中的2项的大型、特征明确、具有全国代表性的医疗保险现行受益人调查（MCBS）队列的成员。从临床角度来看，这条研究路线最终将通过确定具有最佳综合效益的药物，为MCC患者的多药治疗提供循证方法。结果将通过引入新方法、确定有希望的治疗方法来比较MCC患者、确定效应大小和功率估计，为未来的研究提供信息。由于MCBS代表了具有可变MCC组合的全国老年人口，因此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.