Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.
Department of Environmental & Public Health Sciences, College of Medicine, University of Cincinnati, Cincinnati, Ohio, USA.
Clin Exp Allergy. 2024 Mar;54(3):185-194. doi: 10.1111/cea.14452. Epub 2024 Jan 19.
The Learning Early About Peanut Allergy (LEAP) trial showed that early dietary introduction of peanut reduced the risk of developing peanut allergy by age 60 months in infants at high risk for peanut allergy. In this secondary analysis of LEAP data, we aimed to determine risk subgroups within these infants and estimate their respective intervention effects of early peanut introduction.
LEAP raw data were retrieved from ITNTrialShare.org. Conditional random forest was applied to participants in the peanut avoidance arm to select statistically important features for the classification and regression tree (CART) analysis to group infants based on their risk of peanut allergy at 60 months of age. Intervention effects were estimated for each derived risk subgroup using data from both arms. Our main model was generated based on baseline data when the participants were 4-11 months old. Specific IgE measurements were truncated to account for the limit of detection commonly used by laboratories in clinical practice.
The model found infants with higher predicted probability of peanut allergy at 60 months of age had a similar relative risk reduction, but a greater absolute risk reduction in peanut allergy with early introduction of peanut, than those with lower probability. The intervention effects were significant across all risk subgroups. Participants with baseline peanut sIgE ≥0.22 kU/L (n = 78) had an absolute risk reduction of 40.4% (95% CI 27.3, 51.9) whereas participants with baseline peanut sIgE<0.22 kU/L and baseline Ara h 2 sIgE <0.10 kU/L (n = 226) had an absolute risk reduction of 6.5% (95% CI 2.6, 11.0). These findings were consistent in sensitivity analyses using alternative models.
In this study, risk subgroups were determined among infants from the LEAP trial based on the probability of developing peanut allergy and the intervention effects of early peanut introduction were estimated. This may be relevant for further risk assessment and personalized clinical decision-making.
学习早期关于花生过敏(LEAP)试验表明,在高花生过敏风险的婴儿中,早期引入花生的饮食可降低 60 个月时发生花生过敏的风险。在 LEAP 数据的这项二次分析中,我们旨在确定这些婴儿中的风险亚组,并估计他们各自早期引入花生的干预效果。
从 ITNTrialShare.org 检索到 LEAP 原始数据。条件随机森林应用于花生回避组的参与者,以选择用于分类和回归树(CART)分析的统计上重要特征,根据他们在 60 个月时发生花生过敏的风险对婴儿进行分组。使用来自两个臂的数据估计每个派生风险亚组的干预效果。我们的主要模型基于参与者 4-11 个月大时的基线数据生成。由于实验室在临床实践中常用的检测限,特异性 IgE 测量值被截断。
该模型发现,在 60 个月时预测发生花生过敏的概率较高的婴儿,其相对风险降低相似,但早期引入花生后发生花生过敏的绝对风险降低更大。在所有风险亚组中,干预效果均有统计学意义。基线花生 sIgE≥0.22 kU/L(n=78)的参与者绝对风险降低 40.4%(95%CI 27.3,51.9),而基线花生 sIgE<0.22 kU/L 和基线 Ara h 2 sIgE<0.10 kU/L(n=226)的参与者绝对风险降低 6.5%(95%CI 2.6,11.0)。使用替代模型进行的敏感性分析得出了一致的结果。
在这项研究中,根据发生花生过敏的概率,在 LEAP 试验的婴儿中确定了风险亚组,并估计了早期引入花生的干预效果。这可能与进一步的风险评估和个性化临床决策相关。