Section of Inflammation, Repair & Development, National Heart & Lung Institute, Imperial College London, London, UK.
Children's Allergy Dept., Sheffield Children's NHS Foundation Trust, Sheffield, UK.
Clin Exp Allergy. 2020 Mar;50(3):334-342. doi: 10.1111/cea.13577. Epub 2020 Feb 13.
Food allergy diagnosis in clinical studies can be challenging. Oral food challenges (OFC) are time-consuming, carry some risk and may, therefore, not be acceptable to all study participants.
To design and evaluate an algorithm for detecting IgE-mediated food allergy in clinical study participants who do not undergo OFC.
An algorithm for trial participants in the Barrier Enhancement for Eczema Prevention (BEEP) study who were unwilling or unable to attend OFC was developed. BEEP is a pragmatic, multi-centre, randomized-controlled trial of daily emollient for the first year of life for primary prevention of eczema and food allergy in high-risk infants (ISRCTN21528841). We built on the European iFAAM consensus guidance to develop a novel food allergy diagnosis algorithm using available information on previous allergenic food ingestion, food reaction(s) and sensitization status. This was implemented by a panel of food allergy experts blind to treatment allocation and OFC outcome. We then evaluated the algorithm's performance in both BEEP and Enquiring About Tolerance (EAT) study participants who did undergo OFC.
In 31/69 (45%) BEEP and 44/55 (80%) EAT study control group participants who had an OFC the panel felt confident enough to categorize children as "probable food allergy" or "probable no food allergy". Algorithm-derived panel decisions showed high sensitivity 94% (95%CI 68, 100) BEEP; 90% (95%CI 72, 97) EAT and moderate specificity 67% (95%CI 39, 87) BEEP; 67% (95%CI 39, 87) EAT. Sensitivity and specificity were similar when all BEEP and EAT participants with OFC outcome were included.
We describe a new algorithm with high sensitivity for IgE-mediated food allergy in clinical study participants who do not undergo OFC.
This may be a useful tool for excluding food allergy in future clinical studies where OFC is not conducted.
在临床研究中，食物过敏的诊断具有挑战性。口服食物激发试验（OFC）耗时且存在一定风险，因此并非所有研究参与者都能接受。
设计并评估一种适用于未接受 OFC 的临床研究参与者的 IgE 介导的食物过敏检测算法。
为不愿意或不能参加 OFC 的 Barrier Enhancement for Eczema Prevention（BEEP）研究的试验参与者开发了一种算法。BEEP 是一项多中心、随机对照的实用研究，旨在对高危婴儿进行第一年的日常保湿，以预防特应性皮炎和食物过敏（ISRCTN21528841）。我们在欧洲 iFAAM 共识指南的基础上，使用先前致敏食物摄入、食物反应和致敏状态的可用信息，开发了一种新的食物过敏诊断算法。该算法由一组对治疗分配和 OFC 结果均不知情的食物过敏专家进行实施。然后，我们在接受 OFC 的 BEEP 和 Enquiring About Tolerance（EAT）研究参与者中评估了该算法的性能。
在 31/69（45%）名 BEEP 和 44/55（80%）名 EAT 研究对照组参与者中，有 OFC 结果的参与者，专家小组有足够的信心将儿童归类为“可能的食物过敏”或“可能没有食物过敏”。算法得出的专家组决策具有高灵敏度 94%（95%CI 68, 100）BEEP；90%（95%CI 72, 97）EAT 和中等特异性 67%（95%CI 39, 87）BEEP；67%（95%CI 39, 87）EAT。当包括所有接受 OFC 结果的 BEEP 和 EAT 参与者时，灵敏度和特异性相似。
我们描述了一种新的算法，用于检测未接受 OFC 的临床研究参与者中的 IgE 介导的食物过敏，具有高灵敏度。
对于未来不进行 OFC 的临床研究，这可能是一种排除食物过敏的有用工具。
