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Statistical Challenges in the Evaluation of Treatments for Small Patient Populations

机译:小型患者人群治疗评估中的统计挑战

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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.
机译:新疗法的开发通常涉及在大型临床试验中评估其疗效,在该临床试验中,患者被随机分配为新疗法或护理标准。这些大型随机临床试验的结果允许对新疗法相对于标准疗法的临床益处进行明确,公正的评估。对于罕见疾病或在常见疾病范围内确定的小型患者亚组,可能无法进行大型随机试验。在本综述中,我们讨论了替代临床研究设计和统计学上的挑战,这些尝试试图确保研究结果得出有关新医疗产品安全性和有效性的可靠结论。

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