Personalized (N-of-1) Trials for Patient-Centered Treatments of Multimorbidity.

Harvard data science review Pub Date : 2022-01-01 Epub Date: 2022-09-08 DOI:10.1162/99608f92.d99e6ff5
Jerry M Suls, Catherine Alfano, Christina Yap
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引用次数: 1

Abstract

Treatment of patients who suffer from concurrent health conditions is not well served by (1) evidence-based clinical guidelines that mainly specify treatment of single conditions and (2) conventional randomized controlled trials (RCTs) that identify treatments as safe and effective on average. Clinical decision-making based on the average patient effect may be inappropriate for treatment of those with multimorbidity who experience burdens and obstacles that may be unique to their personal situation. We describe how the personalized (N-of-1) trials can be integrated with an automatic platform and virtual/remote technologies to improve patient-centered care for those living with multimorbidity. To illustrate, we present a hypothetical clinical scenario-survivors of both coronavirus disease 2019 (COVID-19) and cancer who chronically suffer from sleeplessness and fatigue. Then, we will describe how the four standard phases of conventional RCT development can be modified for personalized trials and applied to the multimorbidity clinical scenario, outline how personalized trials can be adapted and extended to compare the benefits of personalized trials versus between-subject trial design, and explain how personalized trials can address special problems associated with multimorbidity for which conventional trials are poorly suited.

以患者为中心的多病治疗的个性化(N-of-1)试验
(1)循证临床指南主要规定单一疾病的治疗方法,(2)常规随机对照试验(rct)确定治疗方法的平均安全性和有效性,不能很好地服务于患有并发健康状况的患者。基于平均患者效果的临床决策可能不适合治疗那些经历负担和障碍的多病患者,这些负担和障碍可能是他们个人情况所特有的。我们描述了个性化(N-of-1)试验如何与自动平台和虚拟/远程技术相结合,以改善患有多种疾病的患者的以患者为中心的护理。为了说明这一点,我们提出了一个假设的临床场景——2019年冠状病毒病(COVID-19)和癌症的幸存者长期患有失眠和疲劳。然后,我们将描述如何修改常规RCT开发的四个标准阶段以进行个性化试验并将其应用于多病临床场景,概述如何调整和扩展个性化试验以比较个性化试验与受试者间试验设计的好处,并解释个性化试验如何解决与传统试验不适合的多病相关的特殊问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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