医学
观察研究
心理干预
重症监护医学
随机对照试验
临床试验
干预(咨询)
急性呼吸窘迫
外部有效性
人口
研究设计
治疗效果
护理部
外科
内科学
心理学
社会心理学
社会科学
环境卫生
肺
社会学
传统医学
作者
Emma Graham,Ewan C. Goligher,Matthew W. Semler,Matthew M. Churpek
标识
DOI:10.1097/ccm.0000000000006371
摘要
Critical care trials evaluate the effect of interventions in patients with diverse personal histories and causes of illness, often under the umbrella of heterogeneous clinical syndromes, such as sepsis or acute respiratory distress syndrome. Given this variation, it is reasonable to expect that the effect of treatment on outcomes may differ for individuals with variable characteristics. However, in randomized controlled trials, efficacy is typically assessed by the average treatment effect (ATE), which quantifies the average effect of the intervention on the outcome in the study population. Importantly, the ATE may hide variations of the treatment’s effect on a clinical outcome across levels of patient characteristics, which may erroneously lead to the conclusion that an intervention does not work overall when it may in fact benefit certain patients. In this review, we describe methodological approaches for assessing heterogeneity of treatment effect (HTE), including expert-derived subgrouping, data-driven subgrouping, baseline risk modeling, treatment effect modeling, and individual treatment rule estimation. Next, we outline how insights from HTE analyses can be incorporated into the design of clinical trials. Finally, we propose a research agenda for advancing the field and bringing HTE approaches to the bedside.
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