Clinical application of personalized rheumatoid arthritis risk information: Translational epidemiology leading to precision medicine.
Clinical application of personalized rheumatoid arthritis risk information: Translational epidemiology leading to precision medicine.
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DOI：
10.1080/23808993.2021.1857237
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发表时间：
2021
影响因子：
1.2
通讯作者：
Sparks JA
中科院分区：
文献类型：
--
作者：
Sparks JA
在过去的几十年中，在确定类风湿性关节炎（RA）发展的风险因素方面取得了重大进展，RA是一种相对常见的慢性疾病，其特征是具有复杂病因的炎性关节炎[1]。这些因素包括不可改变的因素，如人口统计学和遗传学[2]，以及潜在的可改变因素，如吸烟和体重指数升高[3]。临床医生可能想知道这些不断增长的知识有一天如何应用于临床实践。流行病学的传统观点使用风险因素被动地阐明整个疾病过程或确定人口水平的趋势。在精准医学的背景下，流行病学研究结果可用于解构疾病异质性[4]，同时为个性化干预措施的开发和实施提供信息[5]，或“转化流行病学”。本文阐述了两项最近的流变学转化流行病学研究，旨在将个性化的风险因素纳入临床框架，使我们更接近精准医学。许多重要的临床风险工具，如心血管疾病的Fragrance风险评分[6]，已经成功实施。虽然这些工具已经过验证，但它们在个体水平[7]或不同人群[6]中可能不准确，并且可能无法纳入新的风险因素或考虑因素之间的相互作用[8]。这些工具通常是为临床医生开发的，以帮助风险分层，筛选，治疗或诊断;它们不太倾向于辅助诊断。虽然遗传因素越来越多地在临床实践中进行测试，但解释通常不容易与其他风险因素相结合。传统的临床风险工具对患者接受干预的意愿、优化健康行为和心理影响的影响尚未成为关注的焦点。因此，传统的临床风险工具不能直接转移到精准医学框架。最近的一项随机对照试验试图调查一年以上慢性病风险的个性化工具对改善健康行为，风险因素知识和心理影响的动机的影响。RA（PRE-RA）家族研究的个性化风险估计开发了一种全面的RA风险工具[9]，将RA风险与人口统计学、家族史、遗传学（HLA-DRB 1“共享表位”，主要的遗传性RA风险因素[10]），生物标志物（两种RA相关血清自身抗体）和四种可改变的RA相关风险行为（吸烟，久坐不动的体力活动，鱼类摄入量低，牙齿卫生差）[11]。基于网络的PRE-RA风险工具提供了关于总体RA风险（使用相对和绝对风险量表）和风险成分/解释的个性化结果[11]。PRERA家族研究随机选择了238名未受影响的RA患者一级亲属，接受个性化风险工具（有或没有健康教育者的额外解释）或关于RA风险的标准非个性化信息[11]。与标准非个性化RA风险信息相比，随机接受个性化RA风险信息披露的参与者有23%（95%置信区间1-51%）更有可能增加改善任何RA风险相关行为（主要结局）的动机，这是一个统计学显著差异[11]。除了动机之外，被分配到个性化组的参与者报告了饮食和牙齿健康行为的显着改善[11]。超过60%的当前吸烟者在PRE-RA工具后6个月戒烟，而当前吸烟者中没有一人...
Over the last few decades, major progress has been made in identifying risk factors for the development of rheumatoid arthritis (RA), a relatively common chronic disease characterized by inflammatory arthritis with complex etiology [1]. These include both nonmodifiable factors, such as demographics and genetics [2], and potentially modifiable factors, such as cigarette smoking and elevated body mass index [3]. Clinicians may wonder how this growing knowledge may someday apply to clinical practice. A traditional view of epidemiology uses risk factors to passively elucidate an overall disease process or identify trends on a population level. In the context of precision medicine, epidemiologic findings may be used to deconstruct disease heterogeneity [4] while informing the development and implementation of personalized interventions [5], or ‘translational epidemiology.’This article illustrates two recent translational epidemiologic studies in rheumatology that sought to incorporate personalized risk factors into a clinical framework leading us closer toward precision medicine. A number of important clinical risk tools, such as the Framingham Risk Score for cardiovascular disease [6], have been successfully implemented. While these tools have been validated, they may be inaccurate on an individual level [7] or in distinct populations [6] and may have no ability to incorporate novel risk factors or consider interactions between factors [8]. These tools were typically developed for clinicians to help risk-stratify, screen, treat, or prognosticate; they were less oriented toward assisting in diagnosis. While genetic factors are increasingly tested in clinical practice, interpretation is usually not easily integrated with other risk factors. The effects of traditional clinical risk tools on the patient’s willingness to accept interventions, optimizing health behaviors, and psychologic impact have not been the focus. Thus, traditional clinical risk tools are not directly transferable toward a precision medicine framework. A recent randomized controlled trial sought to investigate the effects of a personalized tool for chronic disease risk over one year on motivation to improve health behaviors, knowledge of risk factors, and psychologic impact. The Personalized Risk Estimator for RA (PRE-RA) Family Study developed a comprehensive RA risk tool [9] that personalized RA risk to demographics, family history, genetics (HLA-DRB1 ‘shared epitope,’the major genetic RA risk factor [10]), biomarkers (two RA-related serum autoantibodies), and four modifiable RA-related risk behaviors (cigarette smoking, sedentary physical activity, low fish intake, and poor dental hygiene)[11]. The web-based PRE-RA risk tool provided personalized results about overall RA risk (using both relative and absolute risk scales) and the components/explanation of risk [11]. The PRERA Family Study randomized 238 unaffected first-degree relatives of RA patients to receive the personalized risk tool (with or without additional interpretation from a health educator) or standard nonpersonalized information about RA risk [11]. Participants randomized to receive disclosure of personalized RA risk information were 23%(95% confidence interval 1–51%) more likely to increase motivation for improvements in any of the RA risk-related behaviors (the primary outcome) compared to standard nonpersonalized RA risk information, a statistically significant difference [11]. Beyond only motivation, participants assigned to the personalized group reported significant improvements in dietary and dental health behaviors [11]. Over 60% of the current smokers quit smoking by 6 months after the PRE-RA tool, while none of the current smokers …