Division of Biostatistics and Study Methodology, Children's Research Institute at Children's National Medical Center, The George Washington University, Washington, DC, USA.
Orphanet J Rare Dis. 2021 Nov 23;16(1):491. doi: 10.1186/s13023-021-02124-5.
In the United States, approximately 7000 rare diseases affect 30 million patients, and only 10% of these diseases have existing therapies. Sound study design and causal inference methods are essential to demonstrate the therapeutic efficacy, safety, and effectiveness of new therapies. In the rare diseases setting, several factors challenge the use of typical parallel control designs: the small patient population size, genotypic and phenotypic diversity, and the complexity and incomplete understanding of the disorder's progression. Repeated measures, when spaced appropriately relative to disease progression and exploited in design and analysis, can increase study power and reduce variability in treatment effect estimation. This paper reviews these longitudinal designs and draws the parallel between some new and existing randomized studies in rare diseases and their less well-known controlled observational study designs. We show that self-controlled randomized crossover and N-of-1 designs have similar considerations as the observational case series and case-crossover designs. Also, randomized sequential designs have similar considerations to longitudinal cohort studies using sequential matching or weighting to control confounding. We discuss design and analysis considerations for valid causal inference and illustrate them with examples of analyses in multiple rare disorders, including urea cycle disorder and cystic fibrosis.
在美国，约有 7000 种罕见疾病影响着 3000 万名患者，而这些疾病中仅有 10%存在现有疗法。合理的研究设计和因果推断方法对于证明新疗法的治疗效果、安全性和有效性至关重要。在罕见疾病领域，一些因素对典型平行对照设计的应用提出了挑战：患者人群规模小、基因型和表型多样性、疾病进展的复杂性和不完全了解。适当间隔的重复测量，在设计和分析中加以利用，可以提高研究效能并减少治疗效果估计的变异性。本文综述了这些纵向设计，并将一些新的和现有的罕见病随机研究与不太为人知的对照观察性研究设计进行了比较。我们表明，自我对照随机交叉设计和 N-of-1 设计与观察性病例系列和病例交叉设计具有相似的考虑因素。此外，随机序贯设计与使用序贯匹配或加权来控制混杂因素的纵向队列研究具有相似的考虑因素。我们讨论了用于有效因果推断的设计和分析考虑因素，并通过多种罕见疾病（包括尿素循环障碍和囊性纤维化）的分析示例进行了说明。
