Biometric Research Branch, MSC 9735, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA.
Sci Transl Med. 2013 Mar 27;5(178):178sr3. doi: 10.1126/scitranslmed.3004018.
The development of a new treatment typically involves evaluation of its efficacy in a large clinical trial in which patients are randomly assigned either the new treatment or the standard of care. Results from these large randomized clinical trials allow for a definitive and unbiased assessment of the clinical benefit of the new treatment over the standard one. For rare diseases or for small patient subgroups identified within the context of a common disease, it may not be possible to conduct a large randomized trial. In this Review, we discuss alternative clinical study designs and statistical challenges that arise when attempting to assure that study results yield robust conclusions about the safety and effectiveness of a new medical product.
新治疗方法的开发通常需要在一项大型临床试验中评估其疗效，在该试验中，患者被随机分配接受新治疗或标准治疗。这些大型随机临床试验的结果可以对新治疗相对于标准治疗的临床获益进行明确和无偏倚的评估。对于罕见疾病或在常见疾病背景下确定的小患者亚组，可能无法进行大型随机试验。在这篇综述中，我们讨论了在尝试确保研究结果得出关于新医疗产品安全性和有效性的可靠结论时出现的替代临床研究设计和统计挑战。
