Numerous studies have examined the association between pharmacogenetic effects and the response to inhaled corticosteroids (ICS) in patients with asthma. In fact, several single nucleotide polymorphisms of a number of candidate genes have been identified that might influence the clinical response to ICS in children with asthma. Their direct or indirect effects depend on their role in the inflammatory process in asthma or the anti-inflammatory action of corticosteroids, respectively. Among the genes identified, variants in T-box 21 (TBX21) and Fc fragment of IgE receptor II (FCER2) contribute indirectly to the variability in the response to ICS by altering the inflammatory mechanisms in asthma, while other genes such as corticotropin releasing hormone receptor 1 (CRHR1), nuclear receptor subfamily 3 group C member 1 (NR3C1), stress induced phosphoprotein 1 (STIP1), dual specificity phosphatase 1 (DUSP1), glucocorticoid induced 1 (GLCCI1), histone deacetylase 1 (HDAC), ORMDL sphingolipid biosynthesis regulator 3 (ORMDL3), and vascular endothelial growth factors (VEGF) directly affect this variability through the anti-inflammatory mechanisms of ICS. The results to date indicate various potential genetic factors associated with the response to ICS, which could be utilized to predict the individual therapeutic response of children with asthma to ICS. Clinical trials are underway and their results are greatly anticipated. Further pharmacogenetic studies are needed to fully understand the effects of genetic variation on the response to ICS in children with asthma.

ObjectivesTo examine the external validity of the new Fetal Medicine Foundation (FMF) competing risk model for the prediction of small for gestational age (SGA) at 11‐14 weeks of gestation in Asian population.MethodsThis is a secondary analysis of a multicenter prospective cohort study in 10,120 women with singleton pregnancies undergoing routine assessment at 11‐14 weeks of gestation. We applied the FMF competing risk model for the first‐trimester prediction of SGA combining maternal characteristics and medical history with measurements of mean arterial pressure (MAP), uterine artery pulsatility index (UtA‐PI), and serum placental growth factor (PlGF). We obtained risks for different cut‐offs of birth weight percentile and gestational age at delivery. We examined the predictive performance in terms of discrimination and calibration.ResultsThe predictive performance of the competing risk model for SGA was similar to that reported in the FMF study. Specifically, the combination of maternal factors with MAP, UtA‐PI, and PlGF yielded the best performance for the prediction of preterm SGA <10th percentile (SGA<10th) and preterm SGA <5th percentile (SGA<5th), with the areas under the curves (AUCs) of 0.765 (95% confidence interval [CI], 0.720‐0.809) and 0.789 (95%CI, 0.736‐0.841), respectively. Combining maternal factors, MAP, and PlGF yielded the best model for predicting preterm SGA <3rd percentile (SGA<3rd), with an AUC of 0.797 (95%CI, 0.744‐0.850). After excluding preeclampsia (PE) cases, the combination of maternal factors with MAP, UtA‐PI, and PlGF yielded the best performance for the prediction of preterm SGA<10th and SGA<5th, with AUCs of 0.743 (95%CI, 0.691‐0.795) and 0.762 (95%CI, 0.700‐0.824), respectively. However, the best model for predicting preterm SGA<3rd without PE was the combination of maternal factors and PlGF, with an AUC of 0.786 (95%CI, 0.723‐0.849). The FMF competing risk model including maternal factors, MAP, UtA‐PI, PlGF achieved DRs of 42.2%, 47.3%, and 48.1%, at the fixed FPR of 10%, for the prediction of preterm SGA with birth weight <10th, 5th and 3rd percentiles, respectively. The calibration of the new model was satisfactory.ConclusionThe screening performance of the new FMF first trimester competing risk model for SGA in an independent large cohort of Asian women is comparable to that reported in the original FMF study on a mixed European population.This article is protected by copyright. All rights reserved.

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