Optimizing the value of pain management in knee OA patients with comorbidities

指导我们研究的广泛目标是进行分析，为临床医生提供关键的见解 和决策者优化膝骨性关节炎疼痛管理，同时减少膝骨性关节炎患者的阿片类药物使用 主要的合并症包括精神健康障碍和病态肥胖。 症状性膝骨性关节炎(OA)影响着1400多万美国人，每年造成270亿美元的损失 医疗保健支出。传统的认为膝盖骨关节炎疼痛是伤害性的观点受到了进化的挑战 神经系统改变通常会导致敏感化和神经病理性症状的证据。许多 骨性关节炎患者有包括抑郁在内的并发症，这会导致更严重的膝盖疼痛并使疼痛复杂化。 管理，特别是关于阿片类药物的使用。药物只能起到一定的效果，部分原因是它们 并不是为疼痛机制量身定做的。肥胖，尤其是病态肥胖，使两者进一步复杂化 药理学和外科的骨性关节炎疼痛管理。疼痛机制和疼痛频率的多样性 合并症已经开始将膝骨性关节炎重新定义为一种由多种表型组成的综合征，其中 单一的治疗策略并不适用于所有人。 由多种疼痛表型和并发症构成的骨性关节炎疼痛管理方面的挑战，加上 阿片类药物流行的威胁，由于“我们知道的”和“我们做的”之间的差距而进一步加剧。 虽然基于疼痛表型的药物治疗、体重管理和锻炼的有效性 在随机对照试验中建立的这些方法尚未转化为常规护理。动脉压是控制骨性关节炎疼痛的关键， 然而，大多数骨性关节炎患者并不活跃。强有力的证据表明，锻炼和体力活动(PA)是 作为止痛药有效，但运动计划的实施因缺乏 基础设施和资金。合并症增加了缺乏运动的风险，尽管有强有力的证据表明PA 对合并有并发症的骨性关节炎患者有效。疗效的证据不足以促进 将这些方案落实到临床实践中。实施需要投资；需要知识 这些项目的成本效益和预算影响将有助于将研究成果转化为 日常临床管理。 决策分析是一种重要的方法，它有助于评估已经被 被证明是有效的。我们建议使用一个经过验证的膝骨性关节炎计算机模拟模型(OAPol)来 通过评估三种主要治疗策略的价值来缩小证据和实践之间的差距 膝骨性关节炎合并并发症患者的疼痛管理：1)根据疼痛进行量身定制的疼痛管理 表型以优化药物治疗方案；2)改善病态肥胖者的体重管理 以骨性关节炎为重点的治疗结果；以及3)作为非药物止痛方案的PA计划。

The broad objective guiding our research is to conduct analyses that will provide critical insights to clinicians and decision makers to optimize knee OA pain management while reducing opioid use in persons with OA and major comorbidities including mental health disorders and morbid obesity. Symptomatic knee osteoarthritis (OA) affects over 14 million Americans and accounts for $27 billion/year in healthcare expenditures. Traditional views of knee OA pain as nociceptive have been challenged by evolving evidence that nervous system alterations often result in sensitization and neuropathic-like symptoms. Many OA patients have comorbidities including depression, which leads to worse knee pain and complicates pain management, especially regarding opioid use. Medications are only modestly efficacious, in part because they are not tailored to pain mechanisms. Obesity, especially morbid obesity, further complicates both pharmacologic and surgical OA pain management. The diversity of pain mechanisms and frequency of comorbidities have begun to reframe knee OA as a syndrome comprised of multiple phenotypes, wherein a single treatment strategy does not fit all. The challenges in OA pain management posed by multiple pain phenotypes and comorbidities, coupled with the threat of the opioid epidemic, are further exacerbated by the gap between `what we know' and `what we do.' While the efficacy of pain phenotype-based pharmacotherapy, weight management and exercise have been established in RCTs these approaches have not translated to routine care. PA is essential to managing OA pain, yet most OA patients are inactive. Strong evidence suggests that exercise and physical activity (PA) are as effective as analgesic medications, but implementation of exercise programs is hindered by lack of infrastructure and funds. Comorbidities augment the risk of physical inactivity, despite strong evidence that PA is efficacious in OA patients with comorbidities. Evidence of efficacy is not sufficient to facilitate the implementation of these programs into clinical practice. Implementation requires investment; and knowledge of the cost-effectiveness and budgetary impact of these programs will help to translate research findings into day-to-day clinical management. Decision analysis is an important methodology that helps to evaluate the value of programs that have been shown to be efficacious. We propose to use a validated computer simulation model of knee OA (OAPol) to narrow the gap between evidence and practice by assessing the value of three major therapeutic strategies in managing pain in knee OA patients with comorbidities: 1) tailored pain management according to pain phenotypes to optimize pharmacologic regimens; 2) weight management in morbidly obese persons to improve outcomes of OA-focused treatments; and 3) PA programs as non-pharmacologic pain reduction regimens.