个性化营养和肥胖治疗研究中治疗反应异质性的设计、分析和解释。
Design, analysis, and interpretation of treatment response heterogeneity in personalized nutrition and obesity treatment research.
机构信息
Department of Epidemiology and Biostatistics, Indiana University School of Public Health-Bloomington, Bloomington, Indiana, USA.
Glanbia Performance Nutrition, Downers Grove, Illinois, USA.
出版信息
Obes Rev. 2023 Dec;24(12):e13635. doi: 10.1111/obr.13635. Epub 2023 Sep 4.
It is increasingly assumed that there is no one-size-fits-all approach to dietary recommendations for the management and treatment of chronic diseases such as obesity. This phenomenon that not all individuals respond uniformly to a given treatment has become an area of research interest given the rise of personalized and precision medicine. To conduct, interpret, and disseminate this research rigorously and with scientific accuracy, however, requires an understanding of treatment response heterogeneity. Here, we define treatment response heterogeneity as it relates to clinical trials, provide statistical guidance for measuring treatment response heterogeneity, and highlight study designs that can quantify treatment response heterogeneity in nutrition and obesity research. Our goal is to educate nutrition and obesity researchers in how to correctly identify and consider treatment response heterogeneity when analyzing data and interpreting results, leading to rigorous and accurate advancements in the field of personalized medicine.
人们越来越认为，对于肥胖等慢性病的管理和治疗，不存在一种适用于所有人的饮食建议方法。鉴于个性化和精准医学的兴起，这种并非所有个体对给定治疗都能做出一致反应的现象已成为一个研究热点。然而，要严格而科学地开展、解释和传播这项研究，就需要了解治疗反应的异质性。在这里，我们将定义与临床试验相关的治疗反应异质性，提供衡量治疗反应异质性的统计指导，并强调可在营养和肥胖研究中量化治疗反应异质性的研究设计。我们的目标是教育营养和肥胖研究人员，在分析数据和解释结果时如何正确识别和考虑治疗反应的异质性，从而推动个性化医学领域的严谨和准确进展。
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