Statistical Considerations of Food Allergy Prevention Studies

被引:10
|
作者
Bahnson, Henry T. [1 ]
du Toit, George [2 ,3 ]
Lack, Gideon [2 ,3 ]
机构
[1] Benaroya Res Inst, Immune Tolerance Network, Seattle, WA USA
[2] Kings Coll London, Div Asthma Allergy & Lung Biol, Dept Pediat Allergy, London, England
[3] Guys & St Thomas NHS Fdn Trust, London, England
基金
美国国家卫生研究院;
关键词
Prevention studies; Food allergy; Statistical considerations; Complier average causal effect; LEAP; EAT; Dilution effects; Dropout; Imputation; Missing data; Tipping point analysis; Type I error; Type II error; PRINCIPAL STRATIFICATION; CLINICAL-TRIALS; PEANUT ALLERGY; TESTS; POWER; NONCOMPLIANCE; INFANTS; RISK;
D O I
10.1016/j.jaip.2016.12.007
中图分类号
R392 [医学免疫学];
学科分类号
100102 ;
摘要
Clinical studies to prevent the development of food allergy have recently helped reshape public policy recommendations on the early introduction of allergenic foods. These trials are also prompting new research, and it is therefore important to address the unique design and analysis challenges of prevention trials. We highlight statistical concepts and give recommendations that clinical researchers may wish to adopt when designing future study protocols and analysis plans for prevention studies. Topics include selecting a study sample, addressing internal and external validity, improving statistical power, choosing alpha and beta, analysis innovations to address dilution effects, and analysis methods to deal with poor compliance, dropout, and missing data. (C) 2017 The Authors. Published by Elsevier Inc. on behalf of the American Academy of Allergy, Asthma & Immunology.
引用
收藏
页码:274 / 282
页数:9
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