Chow Shein-Chung, Chang Yu-Wei
Department of Biostatistics and Bioinformatics, Duke University School of Medicine , Durham , North Carolina , USA.
Department of Biostatistics, BeiGene, Ltd ., San Mateo , California , USA.
J Biopharm Stat. 2019;29(5):874-886. doi: 10.1080/10543406.2019.1657441. Epub 2019 Aug 27.
One of the most challenges for rare disease clinical trials is probably the availability of a small patient population. It is then a great concern on how to conduct clinical trials with a small number of subjects available for obtaining substantial evidence regarding safety and effectiveness for approval of the rare disease drug product under investigation. FDA, however, does not have the intention to create a statutory standard for approval of orphan drugs that are different from the standard for approval of drugs in common conditions. Thus, it is suggested that innovative trial designs such as a complete n-of-1 trial design or an adaptive design should be used for an accurate and reliable assessment of rare disease drug products under investigation. In this article, basic considerations, innovative trial designs, and statistical methods for data analysis are discussed. In addition, some innovative thinking for the evaluation of rare disease drug products is proposed.
罕见病临床试验面临的最大挑战之一可能是患者群体规模小。因此,如何在受试者数量有限的情况下开展临床试验,以获取充分证据证明正在研究的罕见病药品的安全性和有效性,成为了一个重大问题。然而,美国食品药品监督管理局(FDA)无意为孤儿药的批准制定与普通疾病药物批准标准不同的法定标准。因此,建议采用创新的试验设计,如完全的单病例试验设计或适应性设计,以便对正在研究的罕见病药品进行准确可靠的评估。本文讨论了基本考量、创新试验设计以及数据分析的统计方法。此外,还提出了一些评估罕见病药品的创新思路。