National Academy of Medicine, 500 5th Street NW, Washington, DC, 20001, USA.
Patient-Centered Outcomes Research Institute (PCORI), 1919 M Street NW, Washington, DC, 20036, USA.
Orphanet J Rare Dis. 2018 Jan 19;13(1):14. doi: 10.1186/s13023-017-0755-5.
About 30 million individuals in the United States are living with a rare disease, which by definition have a prevalence of 200,000 or fewer cases in the United States ([National Organization for Rare Disorders], [About NORD], [2016]). Disease heterogeneity and geographic dispersion add to the difficulty of completing robust studies in small populations. Improving the ability to conduct research on rare diseases would have a significant impact on population health. The purpose of this paper is to raise awareness of methodological approaches that can address the challenges to conducting robust research on rare diseases.
We conducted a landscape review of available methodological and analytic approaches to address the challenges of rare disease research. Our objectives were to: 1. identify algorithms for matching study design to rare disease attributes and the methodological approaches applicable to these algorithms; 2. draw inferences on how research communities and infrastructure can contribute to the efficiency of research on rare diseases; and 3. to describe methodological approaches in the rare disease portfolio of the Patient-Centered Outcomes Research Institute (PCORI), a funder promoting both rare disease research and research infrastructure.
We identified three algorithms for matching study design to rare disease or intervention characteristics (Gagne, et.al, BMJ 349:g6802, 2014); (Gupta, et.al, J Clin Epidemiol 64:1085-1094, 2011); (Cornu, et. al, Orphet J Rare Dis 8:48,2012) and summarized the applicable methodological and analytic approaches. From this literature we were also able to draw inferences on how an effective research infrastructure can set an agenda, prioritize studies, accelerate accrual, catalyze patient engagement and terminate poorly performing studies. Of the 24 rare disease projects in the PCORI portfolio, 11 are randomized controlled trials (RCTs) using standard designs. Thirteen are observational studies using case-control, prospective cohort, or natural history designs. PCORI has supported the development of 9 Patient-Powered Research Networks (PPRNs) focused on rare diseases.
Matching research design to attributes of rare diseases and interventions can facilitate the completion of RCTs that are adequately powered. An effective research infrastructure can improve efficiency and avoid waste in rare disease research. Our review of the PCORI research portfolio demonstrates that it is feasible to conduct RCTs in rare disease. However, most of these studies are using standard RCT designs. This suggests that use of a broader array of methodological approaches to RCTs --such as adaptive trials, cross-over trials, and early escape designs can improve the productivity of robust research in rare diseases.
据估计,美国有 3000 万人患有罕见病,根据定义,美国罕见病的患病率为 20 万例或更少([国家罕见病组织],[关于 NORD],[2016])。疾病异质性和地域分散性增加了在小人群中进行稳健研究的难度。提高开展罕见病研究的能力将对人口健康产生重大影响。本文旨在提高对能够解决罕见病研究挑战的方法的认识。
我们对现有的罕见病研究方法和分析方法进行了景观综述,以解决罕见病研究的挑战。我们的目标是:1. 确定匹配研究设计与罕见病属性的算法,以及适用于这些算法的方法;2. 推断研究社区和基础设施如何为罕见病研究的效率做出贡献;3. 描述患者中心的成果研究所 (PCORI) 罕见病组合中的方法,该机构既促进罕见病研究,也促进研究基础设施。
我们确定了三种将研究设计与罕见病或干预特征相匹配的算法(Gagne,等人,BMJ 349:g6802,2014);(Gupta,等人,J Clin Epidemiol 64:1085-1094,2011);(Cornu,等人,Orphet J Rare Dis 8:48,2012)并总结了适用的方法和分析方法。从这些文献中,我们还可以推断出有效的研究基础设施如何能够制定议程、优先考虑研究、加速入组、促进患者参与和终止表现不佳的研究。在 PCORI 组合中的 24 个罕见病项目中,有 11 个是使用标准设计的随机对照试验 (RCT)。十三个是使用病例对照、前瞻性队列或自然历史设计的观察性研究。PCORI 已经支持了 9 个专注于罕见病的患者驱动的研究网络 (PPRN) 的发展。
将研究设计与罕见病和干预措施的特征相匹配,可以促进充分供电的 RCT 的完成。有效的研究基础设施可以提高罕见病研究的效率,避免浪费。我们对 PCORI 研究组合的审查表明,在罕见病中进行 RCT 是可行的。然而,这些研究大多使用标准的 RCT 设计。这表明,在 RCT 中使用更广泛的方法,如适应性试验、交叉试验和早期逃逸设计,可以提高罕见病中稳健研究的生产力。