A Pediatric Asthma Risk Score to better predict asthma development in young children

Investigating Machine Learning Techniques for Predicting Risk of Asthma Exacerbations: A Systematic Review

Asthma, a common chronic respiratory disease among children and adults, affects more than 200 million people worldwide and causes about 450,000 deaths each year. Machine learning is increasingly applied in healthcare to assist health practitioners in decision-making. In asthma management, machine learning excels in performing well-defined tasks, such as diagnosis, prediction, medication, and management. However, there remain uncertainties about how machine learning can be applied to predict asthma exacerbation. This study aimed to systematically review recent applications of machine learning techniques in predicting the risk of asthma attacks to assist asthma control and management. A total of 860 studies were initially identified from five databases. After the screening and full-text review, 20 studies were selected for inclusion in this review. The review considered recent studies published from January 2010 to February 2023. The 20 studies used machine learning techniques to support future asthma risk prediction by using various data sources such as clinical, medical, biological, and socio-demographic data sources, as well as environmental and meteorological data. While some studies considered prediction as a category, other studies predicted the probability of exacerbation. Only a group of studies applied prediction windows. The paper proposes a conceptual model to summarise how machine learning and available data sources can be leveraged to produce effective models for the early detection of asthma attacks. The review also generated a list of data sources that other researchers may use in similar work. Furthermore, we present opportunities for further research and the limitations of the preceding studies.

An integrated molecular risk score early in life for subsequent childhood asthma risk

BACKGROUND

Numerous children present with early wheeze symptoms, yet solely a subgroup develops childhood asthma. Early identification of children at risk is key for clinical monitoring, timely patient-tailored treatment, and preventing chronic, severe sequelae. For early prediction of childhood asthma, we aimed to define an integrated risk score combining established risk factors with genome-wide molecular markers at birth, complemented by subsequent clinical symptoms/diagnoses (wheezing, atopic dermatitis, food allergy).

METHODS

Three longitudinal birth cohorts (PAULINA/PAULCHEN, n = 190 + 93 = 283, PASTURE, n = 1133) were used to predict childhood asthma (age 5-11) including epidemiological characteristics and molecular markers: genotype, DNA methylation and mRNA expression (RNASeq/NanoString). Apparent (ap) and optimism-corrected (oc) performance (AUC/R2) was assessed leveraging evidence from independent studies (Naïve-Bayes approach) combined with high-dimensional logistic regression models (LASSO).

RESULTS

Asthma prediction with epidemiological characteristics at birth (maternal asthma, sex, farm environment) yielded an ocAUC = 0.65. Inclusion of molecular markers as predictors resulted in an improvement in apparent prediction performance, however, for optimism-corrected performance only a moderate increase was observed (upto ocAUC = 0.68). The greatest discriminate power was reached by adding the first symptoms/diagnosis (up to ocAUC = 0.76; increase of 0.08, p = .002). Longitudinal analysis of selected mRNA expression in PASTURE (cord blood, 1, 4.5, 6 years) showed that expression at age six had the strongest association with asthma and correlation of genes getting larger over time (r = .59, p < .001, 4.5-6 years).

CONCLUSION

Applying epidemiological predictors alone showed moderate predictive abilities. Molecular markers from birth modestly improved prediction. Allergic symptoms/diagnoses enhanced the power of prediction, which is important for clinical practice and for the design of future studies with molecular markers.

Filaggrin loss-of-function variants are associated with atopic dermatitis phenotypes in a diverse, early-life prospective cohort

Loss-of-function (LoF) variants in the filaggrin (FLG) gene are the strongest known genetic risk factor for atopic dermatitis (AD), but the impact of these variants on AD outcomes is poorly understood. We comprehensively identified genetic variants through targeted region sequencing of FLG in children participating in the Mechanisms of Progression of Atopic Dermatitis to Asthma in Children cohort. Twenty FLG LoF variants were identified, including 1 novel variant and 9 variants not previously associated with AD. FLG LoF variants were found in the cohort. Among these children, the presence of 1 or more FLG LoF variants was associated with moderate/severe AD compared with those with mild AD. Children with FLG LoF variants had a higher SCORing for Atopic Dermatitis (SCORAD) and higher likelihood of food allergy within the first 2.5 years of life. LoF variants were associated with higher transepidermal water loss (TEWL) in both lesional and nonlesional skin. Collectively, our study identifies established and potentially novel AD-associated FLG LoF variants and associates FLG LoF variants with higher TEWL in lesional and nonlesional skin.

Relationships between lung function, allergy, and wheezing in urban children

BACKGROUND

Allergic sensitization and low lung function in early childhood are risk factors for subsequent wheezing and asthma. However, it is unclear how allergic sensitization affects lung function over time.

OBJECTIVE

We sought to test whether allergy influences lung function and whether these factors synergistically increase the risk of continued wheezing in childhood.

METHODS

We analyzed longitudinal measurements of lung function (spirometry and impulse oscillometry) and allergic sensitization (aeroallergen skin tests and serum allergen-specific IgE) throughout early childhood in the Urban Environmental and Childhood Asthma study, which included high-risk urban children living in disadvantaged neighborhoods. Intraclass correlation coefficients were calculated to assess lung function stability. Cluster analysis identified low, medium, and high allergy trajectories, which were compared with lung function and wheezing episodes in linear regression models. A variable selection model assessed predictors at age 5 years for continued wheezing through age 12 years.

RESULTS

Lung function adjusted for growth was stable (intraclass correlation coefficient, 0.5-0.7) from age 5 to 12 years and unrelated to allergy trajectory. Lung function and allergic sensitization were associated with wheezing episodes in an additive fashion. In children with asthma, measuring lung function at age 5 years added little to the medical history for predicting future wheezing episodes through age 12 years.

CONCLUSIONS

In high-risk urban children, age-related trajectories of allergic sensitization were not associated with lung function development; however, both indicators were related to continued wheezing. These results underscore the importance of understanding early-life factors that negatively affect lung development and suggest that treating allergic sensitization may not alter lung function development in early to mid-childhood.

Component-resolved diagnosis in childhood and prediction of asthma in early adolescence: A birth cohort study

INTRODUCTION

Component-resolved diagnosis (CRD) has been decisive in exploring the mechanisms of IgE sensitization, but the predictive ability to detect asthma has not been addressed. We aim to develop and evaluate the performance of a personalized predictive algorithm for asthma that integrates information on allergic sensitization using CRD.

METHODS

One thousand one hundred one twenty-five children from the Generation XXI birth cohort were randomly selected to perform a screening test for allergic sensitization and a subsample was characterized using CRD against 112 allergen components. Allergen components were analyzed using volcano plots and partial least squares (PLS) analysis. Logistic regression was performed to assess the associations between the obtained latent components (LC) and allergic outcomes (asthma, rhinitis, eczema) including other potential predictors used in previous asthma risk scores. The accuracy of the model in predicting asthma was assessed using Receiver Operating Characteristic (ROC) curve statistics.

RESULTS

In the PLS, the first LC was positively associated with asthma, rhinitis, and eczema. This LC was mainly driven by positive weights for Der p 1/2/23, Der f 1/2, and Fel d 1. The main components in the second LC were pollen and food allergens. History of early wheezing and parental allergy were included in the predictive model and the area under the curve improved to 0.82.

CONCLUSIONS

This is the first approach to improve the clinical applicability of CRD by combining CRD and clinical data to predict asthma at 13 years. Sensitization to distinct allergen molecules seems relevant to improve the accuracy of asthma prediction models.

Severe bronchial hyperresponsiveness along with house dust mite allergy indicates persistence of asthma in young children

BACKGROUND

Significant risk factors for persistence of asthma later in life are family history of allergies, early allergic sensitization and bronchial hyperresponsiveness (BHR). The evolution of BHR in young children without allergic sensitization and with house dust mite allergy (HDM) was investigated.

METHODS

In this retrospective analysis, electronic charts of 4850 young children with asthma and wheezy bronchitis between 2005 and 2018 were reviewed in order to study all patients ≤6 years with BHR assessed by methacholine provocation tests (MCT) at least once (n = 1175). Patients with more than two follow-up measurements were divided in group 1 (no allergic sensitization; n = 110) and group 2 (HDM allergy; n = 88). Additionally, skin prick test, exhaled nitrite oxide (eNO), and asthma treatment were analyzed.

RESULTS

Forty-seven patients of group 1 aged median 4.3 years and 48 patients of group 2 aged median 4.7 years showed initially severe BHR <0.1 mg. At follow-up, patients with HDM were more likely to show persistence of severe BHR than non-sensitized patients (severe BHR group 1: n = 5 (10.6%) vs. group 2: n = 21 (43.8%), p < .001). In addition, 89.4% of group 1 had mild to moderate or no BHR, compared to only 56.2% of group 2. There was a significant difference in eN0 (median group 1: 9 ppb vs. group 2: 26 ppb, p < .001), at last follow-up. Age, sex, and asthma therapy had no effect on BHR.

CONCLUSION

In young children without sensitization BHR normalizes, whereas HDM allergy indicates a persistence of asthma beyond infancy.

Prediction of adult asthma risk in early childhood using novel adult asthma predictive risk scores

BACKGROUND

Numerous risk scores have been developed to predict childhood asthma. However, they may not predict asthma beyond childhood. We aim to create childhood risk scores that predict development and persistence of asthma up to young adult life.

METHODS

The Isle of Wight Birth Cohort (n = 1456) was prospectively assessed up to 26 years of age. Asthma predictive scores were developed based on factors during the first 4 years, using logistic regression and tested for sensitivity, specificity and area under the curve (AUC) for prediction of asthma at (i) 18 and (ii) 26 years, and persistent asthma (PA) (iii) at 10 and 18 years, and (iv) at 10, 18 and 26 years. Models were internally and externally validated.

RESULTS

Four models were generated for prediction of each asthma outcome. ASthma PredIctive Risk scorE (ASPIRE)-1: a 2-factor model (recurrent wheeze [RW] and positive skin prick test [+SPT] at 4 years) for asthma at 18 years (sensitivity: 0.49, specificity: 0.80, AUC: 0.65). ASPIRE-2: a 3-factor model (RW, +SPT and maternal rhinitis) for asthma at 26 years (sensitivity: 0.60, specificity: 0.79, AUC: 0.73). ASPIRE-3: a 3-factor model (RW, +SPT and eczema at 4 years) for PA-18 (sensitivity: 0.63, specificity: 0.87, AUC: 0.77). ASPIRE-4: a 3-factor model (RW, +SPT at 4 years and recurrent chest infection at 2 years) for PA-26 (sensitivity: 0.68, specificity: 0.87, AUC: 0.80). ASPIRE-1 and ASPIRE-3 scores were replicated externally. Further assessments indicated that ASPIRE-1 can be used in place of ASPIRE-2-4 with same predictive accuracy.

CONCLUSION

ASPIRE predicts persistent asthma up to young adult life.

The analysis of risk factors for recurrent wheezing in infants and clinical intervention

Background

Asthma is one of the most common chronic diseases affecting children's health, and recurrent wheezing in infants is closely related to childhood asthma. However, up to now, there is a lack of unified diagnostic criteria and interventions for recurrent wheezing in infants. By analyzing and discussing the risk factors of recurrent wheezing in infants and related intervention measures, we aim to take individualized treatment for different children and reduce the occurrence of recurrent wheezing in infants.

Methods

From January 2017 to December 2020, children under 3 years old who were admitted to the Department of Pediatric Respiratory of Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine with the chief complaint of wheezing for the first time and were clinically diagnosed with bronchiolitis, asthmatic bronchopneumonia and asthmatic bronchitis were retrospectively analyzed through telephone questionnaires. These children were divided into two groups based on whether the wheezing occurred again after discharge. The demographic characteristics, clinical treatment, imaging characteristics, and related interventions and outcomes after discharge were analyzed in both groups.

Results

Among the 523 children under 3 years old who were hospitalized due to wheezing, 264 (50.5%) did not have wheezing after discharge, and 259 (49.5%) still had wheezing after discharge. Both chi-squared test and multivariate analysis showed that male, history of eczema, history of rhinitis, history of wheezing before hospitalization, family smoke exposure, mycoplasma infection and inhalation allergen sensitization were risk factors for recurrent wheezing in infants and young children (P<0.05). Simultaneously, Cox survival curve showed that different intervention time and intervention methods would lead to different prognosis.

Conclusions

(I) Male, with a history of eczema, rhinitis, wheezing before hospitalization, family environment smoke exposure, mycoplasma infection and a history of inhalation allergy are high risk factors for recurrent wheezing in the recurrent wheezing group, and are more likely to have recurrent wheezing after discharge, with shorter days of wheezing control; (II) there was a significant interaction between mycoplasma infection and a history of inhalation allergy in infants with the risk of recurrent wheezing; (III) long-term intervention for children with wheezing for 4 weeks or more after discharge can reduce the probability of recurrent wheezing; (IV) for children of male, with a history of eczema or rhinitis, the most effective intervention to reduce the probability of recurrent wheezing is long-term inhaled corticosteroids (ICS) treatment after discharge.

Performance of the Pediatric Asthma Risk Score across Diverse Populations

BACKGROUND: Methods to determine whether a toddler is likely to develop asthma are of value to parents and clinical trialists testing primary prevention strategies. The Pediatric Asthma Risk Score (PARS) is a 14-point score of six factors designed to predict asthma in early life. PARS was developed and validated in relatively homogenous populations, so its generalizability is unknown. METHODS: We computed PARS using the six factors of self-declared race (parent-reported as “Black” or “not Black”), parental asthma, eczema, any wheezing, wheezing without a cold, and polysensitization in 5634 children from birth to 3 years of age. The primary outcome of our analysis was the ability of PARS to predict asthma development at 5 to 10 years of age using the area under the receiver operating curve in each cohort and across all cohorts with varying ethnicity, sex, cohort type, birth decades, missing PARS factors, and polysensitization definition. We also performed a meta-analysis across all the cohorts. Finally, we compared PARS predictive ability with the binary Asthma Predictive Index (API). RESULTS: Across 10 cohorts, the area under the receiver operating curve for PARS was 0.76. PARS performance did not differ by ethnicity, sex, cohort type, enrollment decade, missing PARS factors, or polysensitization definition (all P>0.05). The weights of each factor in the meta-analysis were similar to the original PARS weights. PARS and API equally identified children at high risk for developing asthma or not; API missed 31% of children at moderate asthma risk. CONCLUSIONS: PARS provided robust estimates of asthma risk in children from a wide range of ethnicities, backgrounds, and susceptibility. (Funded by the National Institute of Allergy and Infectious Diseases and others.)

Developing a prediction model of children asthma risk using population-based family history health records

BACKGROUND

Identifying children at high risk of developing asthma can facilitate prevention and early management strategies. We developed a prediction model of children's asthma risk using objectively collected population-based children and parental histories of comorbidities.

METHODS

We conducted a retrospective population-based cohort study using administrative data from Manitoba, Canada, and included children born from 1974 to 2000 with linkages to ≥1 parent. We identified asthma and prior comorbid condition diagnoses from hospital and outpatient records. We used two machine-learning models: least absolute shrinkage and selection operator (LASSO) logistic regression (LR) and random forest (RF) to identify important predictors. The predictors in the base model included children's demographics, allergic conditions, respiratory infections, and parental asthma. Subsequent models included additional multiple comorbidities for children and parents.

RESULTS

The cohort included 195,666 children: 51.3% were males and 17.7% had asthma diagnosis. The base LR model achieved a low predictive performance with sensitivity of 0.47, 95% confidence interval (0.45-0.48), and specificity of 0.67 (0.66-0.67) using a predicted probability threshold of 0.20. Sensitivity significantly improved when children's comorbidities were included using LASSO LR: 0.71 (0.69-0.72). Predictive performance further improved by including parental comorbidities (sensitivity = 0.72 [0.70-0.73], specificity = 0.69 [0.69-0.70]). We observed similar results for the RF models. Children's menstrual disorders and mood and anxiety disorders, parental lipid metabolism disorders and asthma were among the most important variables that predicted asthma risk.

CONCLUSION

Including children and parental comorbidities to children's asthma prediction models improves their accuracy.

Application of Asthma Prediction Tools in a Cohort of Infants with Severe Bronchiolitis

Background: Severe bronchiolitis is a strong childhood asthma risk factor. Early and accurate asthma prediction is key. We applied the Asthma Predictive Index (API), the modified Asthma Predictive Index (mAPI), and the Pediatric Asthma Risk Score (PARS) in a cohort of high-risk infants to predict asthma at age 6 years. Methods: We conducted a 17-center cohort of infants (age <1 year) hospitalized with severe bronchiolitis during 2011-2014. We used only infancy data to predict asthma at age 6 years. Results: The prevalence of parent-reported asthma at age 6 years was 328/880 (37%). The prevalences of a positive index/score for stringent and loose API, mAPI, and PARS were 21%, 51%, 11%, and 34%, respectively. Area under the receiver operating characteristic curves [95% confidence interval (CI)] ranged from 0.57 (95% CI 0.55-0.60) for mAPI to 0.66 (95% CI 0.63-0.70) for PARS. Conclusions: An asthma prediction tool for high-risk infants is needed to identify those who would benefit most from asthma prevention interventions.

Childhood asthma phenotypes and endotypes: a glance into the mosaic

BACKGROUND

Asthma is an inflammatory lung disease that constitutes the most common noncommunicable chronic disease in childhood. Childhood asthma shows large heterogeneity regarding onset of disease, symptoms, severity, prognosis, and response to therapy.

MAIN BODY

Evidence suggests that this variability is due to distinct pathophysiological mechanisms, which has led to an exhaustive research effort to understand and characterize these distinct entities currently designated as "endotypes." Initially, studies focused on identifying specific groups using clinical variables yielding different "clinical phenotypes." In addition, the identification of specific patterns based on inflammatory cell counts and cytokine data has resulted in "inflammatory endotypes." More recently, an increasing number of molecular data from high-throughput technology ("omics" data) have allowed to investigate more complex "molecular endotypes."

CONCLUSION

A better definition and comprehension of childhood asthma heterogeneity is key for improving diagnosis and treatment. This review aims at summarizing the current knowledge on this topic and discusses some limitations in their application as well as recommendations for future studies.

Assessment of dupilumab in children with moderate-to-severe type 2 asthma with or without evidence of allergic asthma

BACKGROUND

Cytokines, such as interleukins (IL)-4/5/13, play a key role in multiple type 2 inflammatory diseases, including allergic asthma. Dupilumab, a human monoclonal antibody, blocks the shared receptor component for IL-4/IL-13, inhibiting signaling. In this post hoc analysis of VOYAGE (NCT02948959), dupilumab efficacy was evaluated in patients aged 6-11 years with type 2 asthma with or without evidence of allergic asthma (baseline serum total IgE ≥30 IU/mL and ≥1 perennial aeroallergen-specific IgE ≥0.35kU/L).

METHODS

Annualized severe exacerbation rates (AER) and changes in pre-bronchodilator (Pre-BD) forced expiratory volume in one second (FEV1 ), percent-predicted pre-BD FEV1 (ppFEV1 ), and Asthma Control Score (ACQ)-7 were assessed during the treatment period.

RESULTS

350 children (261 with and 89 without evidence of allergic asthma) were included. Dupilumab versus placebo significantly reduced AER in patients with (0.24 vs. 0.62, relative risk reduction [RRR]: 62% [95% CI, 39-76], P < .0001) and without (0.39 vs. 0.80, RRR: 51% [95% CI, 0-76], P < .05) evidence of allergic asthma. Significant improvements in ppFEV1 , pre-bronchodilator FEV1 , and ACQ-7 scores were observed in dupilumab versus placebo throughout the treatment period in patients with evidence of allergic asthma. In patients without evidence of allergic asthma, numerical improvements in pre-bronchodilator FEV1 and asthma control were observed by Week 52.

CONCLUSION

Dupilumab versus placebo reduced asthma exacerbations in children with type 2 asthma irrespective of evidence of allergic asthma; similar trends were observed in changes in lung function. Significant improvement in asthma control was observed in patients with evidence of allergic asthma, but not in those without.

Effect of motivational interviewing on treatment adherence and self-efficacy of adolescents with asthma: A randomized controlled trial

AIMS

This study examined the short-term effect of motivational interviewing on treatment adherence and self-efficacy of adolescents with asthma.

DESIGN

The randomized controlled trial.

METHOD

In this study, 72 adolescents with asthma were recruited and assigned to experimental and control groups randomly. In the experimental group, the motivational interviewing was performed for five weekly sessions lasting 80-90 min. The treatment adherence and self-efficacy questionnaires were completed before the intervention, 2 weeks and 3 months after the intervention in both groups. Data were analysed by Chi-Square test, independent samples T-test, repeated measures of Wilcoxon and generalized estimating equation.

RESULTS

The treatment adherence was found to be significantly higher 2 weeks (p = 0.006) and 3 months after the intervention (p = 0.04) in the experimental group than the control group. In addition, the degree of self-efficacy was significantly more in the experimental group 2 weeks (p < 0.001) and 3 months later (p < 0.001) than the control group. The result of generalized estimating equation showed that the intervention group had an average of 14.44 more self-efficacy points than the control group (p < 0.001). Also, treatment adherence in the intervention group was significantly higher than the control group (β = 6.14, p = 0.05(.

CONCLUSION

This study adds to the evidence for the effectiveness of motivational interviewing in treatment of adolescents with asthma.

Multi-omic factors associated with future wheezing in infants

BACKGROUND

The pathophysiology of wheezing is multifactorial, impacted by medical, demographic, environmental, and immunologic factors. We hypothesized that multi-omic analyses of host and microbial factors in saliva would enhance the ability to identify infants at risk for wheezing.

METHODS

This longitudinal cohort study included 161 term infants. Infants who developed wheezing (n = 27) within 24 months of delivery were identified using the International Study of Asthma and Allergies in Childhood Written Questionnaire and review of the medical record. Standardized surveys were used to assess infant traits and environmental exposures. Saliva was collected for multi-omic assessment of cytokines, microRNAs, mRNAs, and microbiome/virome RNAs.

RESULTS

Two infant factors (daycare attendance, family history of asthma) and three salivary "omic" features (miR-26a-5p, Elusimicrobia, Streptococcus phage phiARI0131-1) differed between the two groups (adjusted p < 0.05). miR-26a-5p levels were correlated with Elusimicrobia (R = -0.87, p = 3.7 × 10^-31). A model employing the three omic features plus daycare attendance and family asthma history yielded the highest predictive accuracy for future wheezing episodes (AUC = 0.74, 95% CI: 0.703-0.772, 77% sensitivity, 62% specificity).

CONCLUSIONS

Host-microbiome interactions in saliva may yield pathophysiologic clues about the origins of wheezing and aid identification of infants at risk of future wheezing episodes.

IMPACT

Wheezing is multi-factorial, but the relative contributions of infant traits, environment, and underlying biology are poorly understood. This multi-omic study identifies three molecular factors, including salivary microRNAs, microbes, and viral phages associated with increased risk of infant wheezing. Measurement of these molecular factors enhanced predictive accuracy for future wheezing when combined with family asthma history and daycare attendance. Validation of this approach could be used to identify infants at risk for wheezing and guide personalized medical management.

Racial Fairness in Precision Medicine: Pediatric Asthma Prediction Algorithms

PURPOSE

Quantify and examine the racial fairness of two widely used childhood asthma predictive precision medicine algorithms: the asthma predictive index (API) and the pediatric asthma risk score (PARS).

DESIGN

Apply the API and PARS and evaluate model performance overall and when stratified by race.

SETTING

Cincinnati, OH, USA.

SUBJECTS

A prospective birth cohort of 590 children with clinically measured asthma diagnosis by age seven.

MEASURES

Model diagnostic criteria included sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

ANALYSIS

Significant differences in model performance between Black and white children were considered to be present if the P-value associated with a t-test based on 100 bootstrap replications was less than .05.

RESULTS

Compared to predictions for white children, predictions for Black children using the PARS had a higher sensitivity (.88 vs .57), lower specificity (.55 vs .83), higher PPV (.42 vs .33), but a similar NPV (.93 vs .93). Within the API and compared to predictions for white children, predictions for Black children had a higher sensitivity (.63 vs .53), similar specificity (.81 vs .80), higher PPV (.54 vs .28), and lower NPV (.86 vs .92).

CONCLUSIONS

Overall, racial disparities in model diagnostic criteria were greatest for sensitivity and specificity in the PARS, but racial disparities existed in three of the four criteria for both the PARS and the API.

Development and validation of a prediction model to predict school-age asthma in preschool children

OBJECTIVE

To develop and validate a clinical prediction model to identify school-age asthma in preschool asthmatic children.

STUDY DESIGN

In this retrospective prognosis cohort study, asthmatic children aged 3-5 years were enrolled with at least 2 years of follow-up, and their potential variables at baseline and the prognosis of school-age asthma were collected from medical records. A clinical prediction model was developed using Logistic regression. The performance of prediction model was assessed and quantified by discrimination of the area under the receiver operating characteristic curve (AUC) and calibration of Brier score. The model was validated by the temporal-validation method.

RESULTS

In the development dataset, 2748 preschool asthmatic children were included for model development, and 883 (32.13%) children were translated to school-age asthma. The independent prognostic variables with an increased risk for school-age asthma were used to develop the prediction model, including: age, parental asthma, early frequent wheezing, allergic rhinitis, eczema, allergic conjunctivitis, obesity, and aeroallergen of dust mite. While assessing model performance, the discrimination power of AUC was moderate [0.788 (0.770-0.805)] with sensitivity (81.5%) and specificity (60.9%), and the calibration of Brier score was 0.169, supporting the calibration ability. In the temporal-validation dataset of 583 preschool asthmatic children, our model showed satisfactory discrimination (AUC 0.818) and calibration (Brier score 0.150). The prediction model was presented by the web-based calculator (https://casthma.shinyapps.io/dynnomapp/) and a nomogram for clinical application.

CONCLUSION

In preschool asthmatic children, our prediction model could be used to predict the risk of school-age asthma.

External validation of the Predicting Asthma Risk in Children tool in a clinical cohort

INTRODUCTION

The Predicting Asthma Risk in Children (PARC) tool uses questionnaire-based respiratory symptoms collected from preschool children to predict asthma risk 5 years later. The tool was developed and validated in population cohorts but not validated using a clinical cohort. We aimed to externally validate the PARC tool in a pediatric pulmonology clinic setting.

METHODS

The Swiss Paediatric Airway Cohort (SPAC) is a prospective cohort of children seen in pediatric pulmonology clinics across Switzerland. We included children aged 1-6 years with cough or wheeze at baseline who completed the 2-year follow-up questionnaire. The outcome was defined as current wheeze plus use of asthma medication. We assessed performance using: sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV), area under the curve (AUC), scaled Brier's score, and Nagelkerke's R² scores. We compared performance in SPAC to that in the original population, the Leicester Respiratory Cohort (LRC).

RESULTS

Among 346 children included, 125 (36%) reported the outcome after 2 years. At a PARC score of 4: sensitivity was higher (95% vs. 79%), specificity lower (14% vs. 57%), and NPV and PPV comparable (0.84 vs. 0.87 and 0.37 vs. 0.42) in SPAC versus LRC. AUC (0.71 vs. 0.78), R² (0.18 vs. 0.28) and Brier's scores (0.13 vs. 0.22) were lower in SPAC.

CONCLUSIONS

The PARC tool shows some clinical utility, particularly for ruling out the development of asthma in young children, but performance limitations highlight the need for new prediction tools to be developed specifically for the clinical setting.

The external validation of the asthma prediction tool in the French ELFE cohort

BACKGROUND

Existing predictive scores for early identification of children at high risk of developing asthma include invasive procedures, and hence have limited utility in a primary care setting. The Leicestershire respiratory cohort (LRC) has developed a noninvasive asthma prediction tool (APT) for children with promising results. We aimed to perform its external validation in the French general population Étude Longitudinale Française depuis l'Enfance (ELFE) cohort.

METHODS

Predictive scores were determined at Age 1 and the primary outcome of asthma was defined as parental reporting of "asthma ever or "wheezing in the past 12 months" at Age 5. Logistic regression was used to calculate the odds ratio (OR) and performance measures, and discriminative performance was reported using the receiver operating curve and area under curve (AUC). Calibration was assessed using Hosmer-Lemeshow goodness-of-fit test and visualized with a calibration plot. Overall performance was determined using Brier scores.

RESULTS

Of the 10,689 children analyzed: 84.9% were at low, 13.1% medium, and 2% at high risk of developing asthma at Age 5. Children in the medium-risk category were three times more likely to develop asthma (OR = 3.3, 95% confidence interval [CI] = 2.97-3.78) whereas 13 times more likely in the high-risk category (OR = 13.8, 95% CI = 10.2-18.8). The tool's AUC was comparable: LRC 0.74 versus ELFE 0.68; as were the Brier scores LRC 0.16 versus ELFE 0.14. The tool's performance was robust to changes in inclusion criteria and outcome definitions.

CONCLUSIONS AND RELEVANCE

Results of the present study and previous validation studies performed in high-risk populations provide a comprehensive measure of the effectiveness of the APT, providing encouragement for its application by general practitioners.

Multiancestral polygenic risk score for pediatric asthma

BACKGROUND

Asthma is the most common chronic condition in children and the third leading cause of hospitalization in pediatrics. The genome-wide association study catalog reports 140 studies with genome-wide significance. A polygenic risk score (PRS) with predictive value across ancestries has not been evaluated for this important trait.

OBJECTIVES

This study aimed to train and validate a PRS relying on genetic determinants for asthma to provide predictions for disease occurrence in pediatric cohorts of diverse ancestries.

METHODS

This study applied a Bayesian regression framework method using the Trans-National Asthma Genetic Consortium genome-wide association study summary statistics to derive a multiancestral PRS score, used one Electronic Medical Records and Genomics (eMERGE) cohort as a training set, used a second independent eMERGE cohort to validate the score, and used the UK Biobank data to replicate the findings. A phenome-wide association study was performed using the PRS to identify shared genetic etiology with other phenotypes.

RESULTS

The multiancestral asthma PRS was associated with asthma in the 2 pediatric validation datasets. Overall, the multiancestral asthma PRS has an area under the curve (AUC) of 0.70 (95% CI, 0.69-0.72) in the pediatric validation 1 and AUC of 0.66 (0.65-0.66) in the pediatric validation 2 datasets. We found significant discrimination across pediatric subcohorts of European (AUC, 95% CI, 0.60 and 0.66), African (AUC, 95% CI, 0.61 and 0.66), admixed American (AUC, 0.64 and 0.70), Southeast Asian (AUC, 0.65), and East Asian (AUC, 0.73) ancestry. Pediatric participants with the top 5% PRS had 2.80 to 5.82 increased odds of asthma compared to the bottom 5% across the training, validation 1, and validation 2 cohorts when adjusted for ancestry. Phenome-wide association study analysis confirmed the strong association of the identified PRS with asthma (odds ratio, 2.71, PFDR = 3.71 × 10-65) and related phenotypes.

CONCLUSIONS

A multiancestral PRS for asthma based on Bayesian posterior genomic effect sizes identifies increased odds of pediatric asthma.

Development of a Symptom-Based Tool for Screening of Children at High Risk of Preschool Asthma

IMPORTANCE

Despite advances in asthma therapeutics, the burden remains highest in preschool children; therefore, it is critical to identify primary care tools that distinguish preschool children at high risk for burdensome disease for further evaluation. Current asthma prediction tools, such as the modified Asthma Predictive Index (mAPI), require invasive tests, limiting their applicability in primary care and low-resource settings.

OBJECTIVE

To develop and evaluate the use of a symptom-based screening tool to detect children at high risk of asthma, persistent wheeze symptoms, and health care burden.

DESIGN, SETTING, AND PARTICIPANTS

The cohort for this diagnostic study included participants from the CHILD Study (n = 2511) from January 1, 2008, to December 31, 2012, the Raine Study from January 1, 1989, to December 31, 2012 (n = 2185), and the Canadian Asthma Primary Prevention Study (CAPPS) from January 1, 1989, to December 31, 1995 (n = 349), with active follow-up to date. Data analysis was performed from November 1, 2019, to May 31, 2022.

EXPOSURES

The CHILDhood Asthma Risk Tool (CHART) identified factors associated with asthma in patients at 3 years of age (timing and number of wheeze or cough episodes, use of asthma medications, and emergency department visits or hospitalizations for asthma or wheeze) to identify children with asthma or persistent symptoms at 5 years of age.

MAIN OUTCOMES AND MEASURES

Within the CHILD Study cohort, CHART was evaluated against specialist clinician diagnosis and the mAPI. External validation was performed in both a general population cohort (Raine Study [Australia]) and a high-risk cohort (CAPPS [Canada]). Predictive accuracy was measured by sensitivity, specificity, area under the receiver operating characteristic curve (AUROC), and positive and negative predicted values.

RESULTS

Among 2511 children (mean [SD] age at 3-year clinic visit, 3.08 [0.17] years; 1324 [52.7%] male; 1608 of 2476 [64.9%] White) with sufficient questionnaire data to apply CHART at 3 years of age, 2354 (93.7%) had available outcome data at 5 years of age. CHART applied in the CHILD Study at 3 years of age outperformed physician assessments and the mAPI in predicting persistent wheeze (AUROC, 0.94; 95% CI, 0.90-0.97), asthma diagnosis (AUROC, 0.73; 95% CI, 0.69-0.77), and health care use (emergency department visits or hospitalization for wheeze or asthma) (AUROC, 0.70; 95% CI, 0.61-0.78). CHART had a similar predictive performance for persistent wheeze in the Raine Study (N = 2185) in children at 5 years of age (AUROC, 0.82; 95% CI, 0.79-0.86) and CAPPS (N = 349) at 7 years of age (AUROC, 0.87; 95% CI, 0.80-0.94).

CONCLUSIONS AND RELEVANCE

In this diagnostic study, CHART was able to identify children at high risk of asthma at as early as 3 years of age. CHART could be easily incorporated as a routine screening tool in primary care to identify children who need monitoring, timely symptom control, and introduction of preventive therapies.

Development and validation of an RNA-seq-based transcriptomic risk score for asthma

Recent progress in RNA sequencing (RNA-seq) allows us to explore whole-genome gene expression profiles and to develop predictive model for disease risk. The objective of this study was to develop and validate an RNA-seq-based transcriptomic risk score (RSRS) for disease risk prediction that can simultaneously accommodate demographic information. We analyzed RNA-seq gene expression data from 441 asthmatic and 254 non-asthmatic samples. Logistic least absolute shrinkage and selection operator (Lasso) regression analysis in the training set identified 73 differentially expressed genes (DEG) to form a weighted RSRS that discriminated asthmatics from healthy subjects with area under the curve (AUC) of 0.80 in the testing set after adjustment for age and gender. The 73-gene RSRS was validated in three independent RNA-seq datasets and achieved AUCs of 0.70, 0.77 and 0.60, respectively. To explore their biological and molecular functions in asthma phenotype, we examined the 73 genes by enrichment pathway analysis and found that these genes were significantly (p < 0.0001) enriched for DNA replication, recombination, and repair, cell-to-cell signaling and interaction, and eumelanin biosynthesis and developmental disorder. Further in-silico analyses of the 73 genes using Connectivity map shows that drugs (mepacrine, dactolisib) and genetic perturbagens (PAK1, GSR, RBM15 and TNFRSF12A) were identified and could potentially be repurposed for treating asthma. These findings show the promise for RNA-seq risk scores to stratify and predict disease risk.

Prevalence of infantile wheezing and eczema in a metropolitan city in Japan: A complete census survey

Infantile wheezing and eczema are associated with the subsequent onset of asthma and other atopic diseases. However, there are no large population-based surveys on infantile allergic symptoms in Japan. The objective of the study was to determine the prevalence of wheezing and asthma in infants in Nagoya, Japan. This population-based cross-sectional study was performed in the metropolitan city of Nagoya, Japan. We surveyed parents to ascertain the prevalence of wheezing and eczema in infants who attended group health checkups at 3, 18, and 36 months of age. Their parents completed modified questionnaires from the International Study of Asthma and Allergies in Childhood. More than 90% of the approximately 40,000 children in each study group living in the target area were included in the survey. The prevalence of wheezing was 8%, 17%, and 13% at 3, 18, and 36 months, respectively, and was characterized by birth season. The prevalence of eczema was 24%, 30%, and 31%, at 3, 18, and 36 months, respectively. Participants born in autumn and winter had a higher incidence of eczema in each age group. Three-quarters of the children had a parental history of allergic conditions. Parental allergic diseases and male gender are risk factors for wheezing and eczema in children. This survey had a high response rate and covered almost the entire population of the target age groups in a large city. We believe that the results of this study, therefore, provide a much higher level of confidence regarding the prevalence of allergies in infants in Japan than that in previous studies with limited cohorts.

Dietary strategies for the prevention of asthma in children

PURPOSE OF REVIEW

This review summarizes information relating to dietary intake during pregnancy, lactation and early life that may prevent childhood asthma. This review also summarizes how future studies may be improved.

RECENT FINDINGS

Recent findings from observational studies suggest that eating according to certain dietary patterns during pregnancy, such as the dietary inflammatory index, Mediterranean diet and Maternal diet index, may reduce asthma and or wheeze in the child. Vitamin D supplementation with higher doses than recommended during pregnancy may be associated with reduced early transient childhood wheezing in the offspring. Higher levels of omega-3 fatty acids in breast milk may be protective against childhood asthma. Breastfeeding infants has been shown to offer many benefits to mother and child but a direct relationship between breastfeeding and the development of asthma has not been established. During childhood, infants and children may need to reduce their intake of advanced glycation end products, increase their food intake according to the traditional Mediterranean diet and increase the diversity of foods eaten.

SUMMARY

Current evidence provides limited suggestions regarding dietary changes for preventing early transient childhood wheezing. In order to harmonize methods for future data collection and reporting, it is important to harmonize relevant definitions and other important factors. The aim of the considerations described here is to enable a better comparison of future studies and provide better guidance to patients and families.

Azithromycin to Prevent Recurrent Wheeze Following Severe Respiratory Syncytial Virus Bronchiolitis

BACKGROUND

Early-life severe respiratory syncytial virus (RSV) bronchiolitis is a risk factor for childhood asthma. Because azithromycin may attenuate airway inflammation during RSV bronchiolitis, we evaluated whether it would reduce the occurrence of post-RSV recurrent wheeze.

METHODS

We prospectively enrolled 200 otherwise healthy 1- to 18-month-old children hospitalized with RSV bronchiolitis in this single-center, double-blind, placebo-controlled study and randomly assigned them to receive oral azithromycin (10 mg/kg daily for 7 days, followed by 5 mg/kg daily for 7 days) or placebo. Randomization was stratified by recent open-label antibiotic use. The primary outcome was the occurrence of recurrent wheeze, defined as a third episode of post-RSV wheeze over the following 2 to 4 years.

RESULTS

As an indication of the biologic activity of azithromycin, nasal wash interleukin-8 levels, at day 14 after randomization, were lower among azithromycin-treated participants (P<0.01). Despite evidence of biologic activity, azithromycin did not reduce the risk of post-RSV recurrent wheeze (47% in the azithromycin group vs. 36% in the placebo group; adjusted hazard ratio, 1.45; 95% confidence interval [CI], 0.92 to 2.29; P=0.11). Azithromycin also did not modify the risk of recurrent wheeze among participants already receiving other antibiotic treatment at the time of enrollment (hazard ratio, 0.94; 95% CI, 0.43 to 2.07). There was a potential signal among antibiotic-naïve participants who received azithromycin to have an increased risk of recurrent wheeze (hazard ratio, 1.79; 95% CI, 1.03 to 3.1).

CONCLUSIONS

Azithromycin therapy for 14 days during acute severe RSV bronchiolitis did not reduce recurrent wheeze occurrence over the following 2 to 4 years. Our data suggest no benefit of azithromycin administration with the goal of preventing recurrent wheeze in later life. (Funded by the National Heart, Lung, and Blood Institute; ClinicalTrials.gov number, NCT02911935.).

Multi-Omics Profiling Approach to Asthma: An Evolving Paradigm

Asthma is a complex multifactorial and heterogeneous respiratory disease. Although genetics is a strong risk factor of asthma, external and internal exposures and their interactions with genetic factors also play important roles in the pathophysiology of asthma. Over the past decades, the application of high-throughput omics approaches has emerged and been applied to the field of asthma research for screening biomarkers such as genes, transcript, proteins, and metabolites in an unbiased fashion. Leveraging large-scale studies representative of diverse population-based omics data and integrating with clinical data has led to better profiling of asthma risk. Yet, to date, no omic-driven endotypes have been translated into clinical practice and management of asthma. In this article, we provide an overview of the current status of omics studies of asthma, namely, genomics, transcriptomics, epigenomics, proteomics, exposomics, and metabolomics. The current development of the multi-omics integrations of asthma is also briefly discussed. Biomarker discovery following multi-omics profiling could be challenging but useful for better disease phenotyping and endotyping that can translate into advances in asthma management and clinical care, ultimately leading to successful precision medicine approaches.

Dietary Intake and Asthma in Preschoolers: A Logistic Lasso Regression Analysis

BACKGROUND

Asthma is a common chronic disease among children, especially preschoolers. Some evidence suggests that diet may play a role in asthma, but the current findings are contradictory. The objective of our study was to determine the association between dietary intake and asthma in preschool children aged 2-5 years.

METHODS

We selected preschool children aged 2-5 years with complete data on asthma diagnosis, diet, and body mass index (BMI) from the national health and nutrition examination survey (NHANES) database. In a selected population, children with self-reported asthma were included in the final sample. In children without self-reported asthma, we further used propensity score matching (PSM) to match age and sex for sampling, maintaining a ratio of 1:4 for cases. Lasso regression was used to identify dietary factors affecting asthma in preschoolers.

RESULTS

A total of 269 children with self-reported asthma and 1,076 children without self-reported asthma were included in our study. Univariate analysis showed that there were significant differences in ethnicity and dietary zinc intake between asthmatic children and children without asthma. After adjusting for all dietary and demographic variables, the results of logistic Lasso regression analysis showed that non-Hispanic black (β = 0.65), vitamin B12 (β = 0.14), and sodium (β = 0.05) were positively associated with childhood asthma, while Vitamin K (β = -0.04) was negatively associated with childhood asthma.

CONCLUSION

In conclusion, our study confirms that non-Hispanic black and dietary sodium intake are associated with a higher risk of asthma in preschoolers. In addition, our study found that dietary vitamin B12 was positively associated with childhood asthma, while vitamin K was negatively associated with childhood asthma.

Visualizing the knowledge domains and research trends of childhood asthma: A scientometric analysis with CiteSpace

BACKGROUND

Asthma is one of the most common chronic diseases in children globally. In recent decades, advances have been made in understanding the mechanism, diagnosis, treatment and management for childhood asthma, but few studies have explored its knowledge structure and future interests comprehensively.

OBJECTIVE

This scientometric study aims to understand the research status and emerging trends of childhood asthma.

METHODS

CiteSpace (version 5.8.R3) was used to demonstrate national and institutional collaborations in childhood asthma, analyze research subjects and journal distribution, review research keywords and their clusters, as well as detect research bursts.

RESULTS

A total of 14,340 publications related to childhood asthma were extracted from Web of Science (core database) during January 2011 to December 2021. The results showed that academic activities of childhood asthma had increased steadily in the last decade. Most of the research was conducted by developed countries while China, as a developing country, was also actively engaged in this field. In addition to subjects of allergy and immunology, both public health aspects and ecological environmental impacts on the disease were emphasized recently in this research field. Keywords clustering analysis indicated that research on asthma management and atopy was constantly updated and became the two major research focuses recently, as a significant shift in research hotspots from etiology and diagnosis to atopic march and asthma management was identified. Subgroup analysis for childhood asthma management and atopy suggested that caregiver- or physician-based education and interventions were emerging directions for asthma management, and that asthma should be carefully studied in the context of atopy, together with other allergic diseases.

CONCLUSIONS

This study presented a comprehensive and systematic overview of the research status of childhood asthma, provided clues to future research directions, and highlighted two significant research trends of asthma management and atopy in this field.

Childhood asthma : factors predicting severity and persistence of symptoms

BACKGROUND

Asthma is the most common chronic disease in infants. In young children, asthma still raises many questions and many points are still being debated.

AIM

The aim of this study is to identifies, in asthmatic children, factors predictors of severity and persistence of symptoms.

METHODS

A retrospective study of asthmatic infants<3 years enrolled in the pediatric department of Sfax over a period of 5 years (2007-2011). We were interested to social and environmental factors, the allergic background, clinical severity of the disease, results of allergic skin tests, treatment and respiratory outcome.

RESULTS

We collected 180 children with a sex ratio of 2.2. Family history of atopy and exposition to passive tobacco were noted in 45 % and 52% of cases respectively. The mean age of onset of wheezing was 6.6 months. Skin tests were positives in 32% of cases. At the time of diagnosis, asthma was classified intermittent (21%), mild to moderate (55.6%) and severe (22.2%).  Inhaled corticosteroids was initiated in 142 infants (78.8%). Skin tests performed in 84 patients, were positive in 32%. Factors associated with severe asthma were passive smoking, early age of onset, number of hospitalizations for exacerbation and existence of an aggravating factor. Factors predictors of persistence were an early age of onset, caesarean delivery, passive smoking and positive skin tests.

CONCLUSION

Factors associated with persistence of asthma at the individual level remains uncertain. However, atopy and passive smoking are major indicators.

Associated factors with recurrent wheezing in infants: is there difference between the sexes?

OBJECTIVE

Identify associated factors for recurrent wheezing (RW) in male and female infants.

METHODS

Cross-sectional multicentric study using the standardized questionnaire from the Estudio Internacional sobre Sibilancias en Lactantes (EISL). The questionnaire was applied to parents of 9345 infants aged 12-15 months at the time of immunization/routine visits.

RESULTS

One thousand two hundred and sixty-one (13.5%) males and nine hundred sixty-three (10.3%) females have had RW (≥3 episodes), respectively (p10 colds episodes (OR = 3.46; IC 95% 2.35-5.07), air pollution (OR = 1.33; IC 95% 1.12-1.59), molds at home (OR = 1.23; IC 95% 1.03-1.47), Afro-descendants (OR = 1.42; IC 95% 1.20-1.69), bronchopneumonia (OR = 1.41; IC; 1.11-1.78), severe episodes of wheezing in the first year (OR = 1.56; IC 95% 1.29-1.89), treatment with bronchodilators (OR = 1.60; IC 95% 1.22-2,1) and treatment with oral corticosteroids (OR = 1,23; IC 95% 0.99-1,52). Associated factors for RW for females were passive smoking (OR = 1.24; IC 95% 1.01-1,51), parents diagnosed with asthma (OR = 1.32; IC 95% 1,08-1,62), parents with allergic rhinitis (OR = 1.26; IC 95% 1.04-1.53), daycare attendance (OR = 1.48; IC 95% 1.17-1,88), colds in the first 6 months of life (OR = 2.19; IC 95% 1.69-2.82), personal diagnosis of asthma (OR = 1.84; IC 95% 1.39-2.44), emergency room visits (OR = 1.78; IC 95% 1.44-2.21), nighttime symptoms (OR = 2.89; IC 95% 2.34-3.53) and updated immunization (OR = 0.62; IC 95% 0.41-0.96).

CONCLUSION

There are differences in associated factors for RW between genders. Identification of these differences could be useful to the approach and management of RW between boys and girls.

Development of childhood asthma prediction models using machine learning approaches

BACKGROUND

Respiratory symptoms are common in early life and often transient. It is difficult to identify in which children these will persist and result in asthma. Machine learning (ML) approaches have the potential for better predictive performance and generalisability over existing childhood asthma prediction models. This study applied ML approaches to predict school-age asthma (age 10) in early life (Childhood Asthma Prediction in Early life, CAPE model) and at preschool age (Childhood Asthma Prediction at Preschool age, CAPP model).

METHODS

Clinical and environmental exposure data was collected from children enrolled in the Isle of Wight Birth Cohort (N = 1368, ∼15% asthma prevalence). Recursive Feature Elimination (RFE) identified an optimal subset of features predictive of school-age asthma for each model. Seven state-of-the-art ML classification algorithms were used to develop prognostic models. Training was performed by applying fivefold cross-validation, imputation, and resampling. Predictive performance was evaluated on the test set. Models were further externally validated in the Manchester Asthma and Allergy Study (MAAS) cohort.

RESULTS

RFE identified eight and twelve predictors for the CAPE and CAPP models, respectively. Support Vector Machine (SVM) algorithms provided the best performance for both the CAPE (area under the receiver operating characteristic curve, AUC = 0.71) and CAPP (AUC = 0.82) models. Both models demonstrated good generalisability in MAAS (CAPE 8-year = 0.71, 11-year = 0.71, CAPP 8-year = 0.83, 11-year = 0.79) and excellent sensitivity to predict a subgroup of persistent wheezers.

CONCLUSION

Using ML approaches improved upon the predictive performance of existing regression-based models, with good generalisability and ability to rule in asthma and predict persistent wheeze.

Performance of Three Asthma Predictive Tools in a Cohort of Infants Hospitalized With Severe Bronchiolitis

Childhood asthma develops in 30–40% of children with severe bronchiolitis but accurate prediction remains challenging. In a severe bronchiolitis cohort, we applied the Asthma Predictive Index (API), the modified Asthma Predictive Index (mAPI), and the Pediatric Asthma Risk Score (PARS) to predict asthma at age 5 years. We applied the API, mAPI, and PARS to the 17-center cohort of infants hospitalized with severe bronchiolitis during 2011–2014 (35th Multicenter Airway Research Collaboration, MARC-35). We used data from the first 3 years of life including parent interviews, chart review, and specific IgE testing to predict asthma at age 5 years, defined as parent report of clinician-diagnosed asthma. Among 875/921 (95%) children with outcome data, parent-reported asthma was 294/875 (34%). In MARC-35, a positive index/score for stringent and loose API, mAPI, and PARS were 24, 68, 6, and 55%, respectively. The prediction tools' AUCs (95%CI) ranged from 0.57 (95%CI 0.54–0.59) to 0.68 (95%CI 0.65–0.71). The positive likelihood ratios were lower in MARC-35 compared to the published results from the original cohorts. In this high-risk population of infants hospitalized with severe bronchiolitis, API, mAPI, and PARS had sub-optimal performance (AUC &lt;0.8). Highly accurate (AUC &gt;0.8) asthma prediction tools are desired in infants hospitalized with severe bronchiolitis.

Longitudinal atopic dermatitis endotypes: An atopic march paradigm that includes Black children

BACKGROUND

The atopic march has been studied mostly in White populations, biasing our current paradigms.

OBJECTIVE

We sought to define the atopic march in Black and White children and explore mechanisms for racial differences.

METHODS

Utilizing the Mechanisms of Progression of Atopic Dermatitis to Asthma in Children (MPAACH) cohort (n = 601), we assessed longitudinal sensitization, food allergy (FA), allergic rhinitis, risk of asthma development (through the Pediatric Asthma Risk Score), Scoring for Atopic Dermatitis (SCORAD), transepidermal water loss, skin filaggrin (FLG) expression, exposures, and genetic heritability to define AD progression endotypes in Black and White children.

RESULTS

White MPAACH children were more likely to be sensitized to aero and food allergens (P = .0001) and over 3 times more likely to develop FA and/or allergic rhinitis (AR) without asthma risk (P < .0001). In contrast, Black children were over 6 times more likely to proceed to high asthma risk without FA, sensitization, or AR (P < .0001). White children had higher lesional and nonlesional transepidermal water loss (both P < .001) as well as decreased nonlesional keratinocyte FLG expression (P = .02). Black children had increased genetic heritability for asthma risk and higher rates of exposures to secondhand smoke and traffic-related air pollution.

CONCLUSIONS

Black and White children with AD have distinct allergic trajectories defined by different longitudinal endotypes. Black children exhibit higher asthma risk despite a more intact skin barrier and less sensitization, FA, and AR. White children have less asthma risk, despite a more dysfunctional skin barrier, and more FA, AR, and sensitization. The observed racial differences are likely due in part to increased genetic heritability for asthma risk and harmful environmental exposures in Black children. Collectively, our findings provide a new paradigm for an atopic march that is inclusive of Black children.

Advances in asthma: New understandings of asthma's natural history, risk factors, underlying mechanisms, and clinical management

The last 2 years yielded a proliferation of high-quality asthma research. These include new understandings of the incidence and natural history of asthma, findings on the effects of exposure to air pollution, allergens, and intake of acetaminophen, soy isoflavones, and polyunsaturated fatty acids, and exposure to microbial products. The past 2 years have benefited from great strides in determining potential mechanisms of asthma development and asthma exacerbations. These novel understandings led to identification and development of exciting new avenues for potential therapeutic intervention. Finally, there has been significant progress made in the development of tools to facilitate the diagnosis of asthma and measurement of airway physiology and in precision diagnostic approaches. Asthma guidelines were updated and new insights into the pharmacologic management of patients, including biologics, were reported. We review the most notable advances in the natural history of asthma, risk factors for the development of asthma, underlying mechanisms, diagnostic approaches, and treatments. Although greater knowledge of the mechanisms underlying responses and nonresponses to novel therapeutics and across asthma phenotypes would be beneficial, the progress over just the past 2 years has been immense and impactful.

Decision tree-based rules outperform risk scores for childhood asthma prognosis

BACKGROUND

There are no widely accepted prognostic tools for childhood asthma; this is in part due to the multifactorial and time-dependent nature of mechanisms and risk factors that contribute to asthma development. Our study objective was to develop and evaluate the prognostic performance of conditional inference decision tree-based rules using the Pediatric Asthma Risk Score (PARS) predictors as an alternative to the existing logistic regression-based risk score for childhood asthma prediction at 7 years in a high-risk population.

METHODS

The Canadian Asthma Primary Prevention Study data were used to develop, compare, and contrast the prognostic performance (area under the curve [AUC], sensitivity, and specificity) of conditional inference tree-based decision rules to the pediatric asthma risk score for the prediction of childhood asthma at 7 years.

RESULTS

Conditional inference decision tree-based rules have higher prognostic performance (AUC: 0.85; 95% CI: 0.81, 0.88; sensitivity = 47%; specificity = 93%) than the pediatric asthma risk score at an optimal cutoff of ≥6 (AUC: 0.71; 95% CI: 0.67, 0.76; sensitivity = 60%; specificity = 74%). Moreover, the pediatric asthma risk score is not linearly related to asthma risk, and at any given pediatric asthma risk score value, different combinations of its pediatric asthma risk score clinical variables differentially predict asthma risk.

CONCLUSION

Conditional inference tree-based decision rules could be a useful childhood asthma prognostic tool, providing an alternative way to identify unique subgroups of at-risk children, and insights into associations and effect mechanisms that are suggestive of appropriate tailored preventive interventions. However, the feasibility and effectiveness of such decision rules in clinical practice is warranted.

Evaluation of Risk Scores to Predict Pediatric Severe Asthma Exacerbations

BACKGROUND

Asthma exacerbations commonly lead to unplanned health care utilization and are costly. Early identification of children at increased risk of asthma exacerbations would allow a proactive management approach.

OBJECTIVE

We evaluated common asthma risk factors to predict the probability of exacerbation for individual children aged 0-21 years using data from the electronic medical record (EMR).

METHODS

We analyzed longitudinal EMR data for over 3000 participants with asthma seen at Cincinnati Children's Hospital Medical Center over a 7-year period. The study population was divided into 3 age groups: 0-4, 5-11, and 12-21 years. Each age group was divided into a derivation cohort and a validation cohort, which were used to build a risk score model. We predicted risk of exacerbation in the next 12 months, validated the scores by risk stratum, and developed a clinical tool to determine the risk level based on this model.

RESULTS

Risk model results were confirmed with validation cohorts by calendar year and age groups. Race, allergic sensitization, and smoke exposure were each important risk factors in the 0-4 age group. Abnormal spirometry and obesity were more sensitive predictors of exacerbation in children >12 years. For each age group, a higher expanded score was associated with a higher predicted probability of an asthma exacerbation in the subsequent year.

CONCLUSION

This asthma exacerbation prediction model, and the associated clinical tool, may assist clinicians in identifying children at high risk for exacerbation that may benefit from more aggressive management and targeted risk mitigation.

Phenotypes of atopic dermatitis and the risk for subsequent asthma: a systematic review and meta-analysis

BACKGROUND

Various atopic dermatitis (AD) phenotypes showed an enormously heterogenic risk for subsequent asthma development.

OBJECTIVE

We aimed to investigate the association between AD phenotypes and the risk for progression to asthma.

METHODS

We searched PubMed, Embase, and Web of Science databases for relevant publications. Pooled relative risks (RR) with 95% confidence intervals (CI) were calculated using the CMA-3.0 software. This study has been registered with PROSPERO (CRD42019129273).

RESULTS

We analyzed 39 publications with 458,810 participants. The RR for asthma in AD was 2.16 (95% CI, 1.88-2.48). The risk in persistent AD (RR, 3.36; 95% CI, 2.83-3.99) was higher than in transient AD (RR, 1.52; 95% CI, 1.34-1.73), and in severe AD (RR, 2.40; 95% CI, 1.96-2.94) was higher than mild (RR, 1.82; 95% CI, 1.03-3.23) or moderate (RR, 1.51; 95% CI, 1.30-1.75) AD. The risk for asthma in early-onset AD was slightly higher than in late-onset AD and in boys higher than girls.

LIMITATIONS

The AD and asthma definitions differed across the included studies.

CONCLUSION

Patients with persistent or severe AD were at a higher risk for developing asthma. These findings further elucidate the atopic march and identify target populations for asthma prevention.

Genetic ancestry differences in pediatric asthma readmission are mediated by socioenvironmental factors

BACKGROUND

Social and financial hardships, combined with disease managment and environmental factors explain approximately 80% of the observed disparity in asthma-related readmissions between Black and White children.

OBJECTIVE

We sought to determine whether asthma-related readmissions differed by degree of African ancestry and the extent to which such an association would also be explained by socioenvironmental risk factors.

METHODS

This study used data from a prospective cohort study of 695 Black and White children aged 1 to 16 years with an asthma-related admission. The primary outcome was a similar readmission within 12 months. Each subject's African ancestry was determined by single nucleotide polymorphisms on a continuous scale ranging from 0 to 1 (0 = no African ancestry; 1 = 100% African ancestry). We also assessed 37 social, environmental, and clinical variables that we clustered into 6 domains (for example, hardship, disease management). Survival and mediation analyses were conducted.

RESULTS

A total of 134 children (19.3%) were readmitted within 12 months. Higher African ancestry was associated with asthma readmission (odds ratio 1.11, 95% confidence interval 1.05-1.18 for every 10% increase in African ancestry) with adjustment for age and gender. The association between African ancestry and readmission was mediated by hardship (sβ = 3.42, P < .001) and disease management (sβ = 0.046, P = .001), accounting for >50% of African ancestry's effect on readmission. African ancestry was no longer significantly associated with readmission (sβ = 0.035, P = .388) after accounting for these mediators.

CONCLUSIONS

African ancestry was strongly associated with readmission, and the association was mediated by family hardship and disease management. These results are consistent with the notion that asthma-related racial disparities are driven by factors like structural racism and social adversity.

Predicting Severe Asthma Exacerbations in Children: Blueprint for Today and Tomorrow

Severe asthma exacerbations are the primary cause of morbidity and mortality in children with asthma. Accurate prediction of children at risk for severe exacerbations, defined as those requiring systemic corticosteroids, emergency department visit, and/or hospitalization, would considerably reduce health care utilization and improve symptoms and quality of life. Substantial progress has been made in identifying high-risk exacerbation-prone children. Known risk factors for exacerbations include demographic characteristics (ie, low income, minority race/ethnicity), poor asthma control, environmental exposures (ie, aeroallergen exposure/sensitization, concomitant viral infection), inflammatory biomarkers, genetic polymorphisms, and markers from other "omic" technologies. The strongest risk factor for a future severe exacerbation remains having had one in the previous year. Combining risk factors into composite scores and use of advanced predictive analytic techniques such as machine learning are recent methods used to achieve stronger prediction of severe exacerbations. However, these methods are limited in prediction efficiency and are currently unable to predict children at risk for impending (within days) severe exacerbations. Thus, we provide a commentary on strategies that have potential to allow for accurate and reliable prediction of children at risk for impending exacerbations. These approaches include implementation of passive, real-time monitoring of impending exacerbation predictors, use of population health strategies, prediction of severe exacerbation responders versus nonresponders to conventional exacerbation management, and considerations for preschool-age children who can be especially high risk. Rigorous prediction and prevention of severe asthma exacerbations is needed to advance asthma management and improve the associated morbidity and mortality.

Which Wheezing Preschoolers Should be Treated for Asthma?

Wheezing disorders in children younger than 5 years are common, but lack of clarity remains about which children should be treated to prevent symptoms and acute episodes. The aim of this review was to discuss a practical approach to deciding which children younger than 5 years with asthma should be treated, and if so, with which strategy. The importance of having a clear definition of "asthma" for this age group, determined by a collection of presenting respiratory symptoms, without assumptions about underlying mechanisms is addressed. Subsequent consideration should be given to timing, severity, and frequency of symptoms, together with assessment of objective biomarkers, including aeroallergen sensitization and blood eosinophils, to inform whether or not a preschooler with recurrent wheezing requires treatment. Numerous unanswered questions remain about the optimal management of nonallergic preschool wheezing and asthma, and areas of specific unmet need and future directions for research are highlighted.

A randomized trial of subcutaneous allergy immunotherapy in inner-city children with asthma less than 4 years of age

BACKGROUND

Allergic sensitization to environmental allergens in the first years of life is a strong predictor of asthma morbidity in children. Allergy immunotherapy can improve asthma and allergy outcomes, but its efficacy in inner-city, atopic children of less than 4 years of age with recurrent wheezing has not yet been established.

OBJECTIVE

To determine whether subcutaneous allergy immunotherapy improves asthma in a population of US inner-city children when started at less than 4 years of age.

METHODS

In a randomized controlled, open-label phase I-II single-center trial in the Bronx, New York, 58 children with recurrent wheezing or physician-diagnosed asthma were randomized to receive asthma standard of care treatment with or without a 3-year course of multiple allergen subcutaneous immunotherapy.

RESULTS

A total of 23 children in the control group and 27 children in the immunotherapy group began the study. A total of 20 of 27 children commencing immunotherapy completed at least 2 years of immunotherapy. There was no difference in asthma medication and symptom scores between the treatment or control groups over time. Similarly, naso-ocular symptoms and allergy medication use were similar in both groups over time. Nevertheless, asthma-related quality of life improved in the immunotherapy group compared with the control group (P = .03).

CONCLUSION

With the exception of asthma-related quality of life, allergy immunotherapy was ineffective in improving asthma outcomes in this population of inner-city children of less than 4 years of age. These findings suggest that the effects of allergy immunotherapy depend on population-specific factors and highlight the importance of precise predictors of immunotherapy efficacy.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT01028560.

Prediction models for childhood asthma: A systematic review

BACKGROUND

The inability to objectively diagnose childhood asthma before age five often results in both under-treatment and over-treatment of asthma in preschool children. Prediction tools for estimating a child's risk of developing asthma by school-age could assist physicians in early asthma care for preschool children. This review aimed to systematically identify and critically appraise studies which either developed novel or updated existing prediction models for predicting school-age asthma.

METHODS

Three databases (MEDLINE, Embase and Web of Science Core Collection) were searched up to July 2019 to identify studies utilizing information from children ≤5 years of age to predict asthma in school-age children (6-13 years). Validation studies were evaluated as a secondary objective.

RESULTS

Twenty-four studies describing the development of 26 predictive models published between 2000 and 2019 were identified. Models were either regression-based (n = 21) or utilized machine learning approaches (n = 5). Nine studies conducted validations of six regression-based models. Fifteen (out of 21) models required additional clinical tests. Overall model performance, assessed by area under the receiver operating curve (AUC), ranged between 0.66 and 0.87. Models demonstrated moderate ability to either rule in or rule out asthma development, but not both. Where external validation was performed, models demonstrated modest generalizability (AUC range: 0.62-0.83).

CONCLUSION

Existing prediction models demonstrated moderate predictive performance, often with modest generalizability when independently validated. Limitations of traditional methods have shown to impair predictive accuracy and resolution. Exploration of novel methods such as machine learning approaches may address these limitations for future school-age asthma prediction.

IL-22/IL-22R1 promotes proliferation and collagen synthesis of MRC-5 cells via the JAK/STAT3 signaling pathway and regulates airway subepithelial fibrosis

Asthma in children poses a threat to their health, but the mechanism remains to be elucidated. The present study investigated the mechanism by which the interleukin (IL)-22/IL-22 receptor 1 (IL-22R1) signaling pathway regulates subepithelial fibrosis in children with asthma. A total of 41 children with asthma and 12 healthy children were included in the present study. ELISA was performed to measure the content of IL-22 in peripheral blood. Serum from children with asthma was used to incubate MRC-5 cells and IL-22 antibody rescued the effect of IL-22 on the biological functions of MRC-5 cells. Reverse transcription-quantitative PCR was performed to determine IL-22R1 mRNA expression levels and western blotting was performed to measure IL-22R1 protein expression. The Cell Counting Kit-8 assay was used to analyze cell proliferation and flow cytometry was performed to assess the cell cycle distribution of MRC-5 cells. The expression of IL-22 was elevated in peripheral blood from children with asthma, which promoted the proliferation of MRC-5 cells, possibly via the upregulation of collagen type I α1 chain (COL1α1) and collagen type I α2 chain (COL1α2). IL-22 exerted its biological functions via IL-22R1. The IL-22/IL-22R1 signaling pathway regulated the proliferation of MRC-5 cells and the expression of COL1α1 and COL1α2 in MRC-5 cells via the JAK/STAT3 signaling pathway. Mononuclear lymphocytes from children with asthma stimulated the proliferation and secretory function of fibroblasts by secreting IL-22. The present study suggested that IL-22 expression in peripheral blood of children with asthma is upregulated compared with the control group. Furthermore, the present study indicated that the IL-22/IL-22R1 signaling pathway promoted MRC-5 cell proliferation and collagen synthesis by activating the JAK/STAT3 signaling pathway, thereby potentially regulating airway subepithelial fibrosis.

Prevention and treatment of recurrent viral-induced wheezing in the preschool child

OBJECTIVE

To summarize the recent evidence in the treatment of viral-induced wheezing in the infant and preschool aged child.

DATA SOURCES

Published literature obtained through PubMed database searches.

STUDY SELECTIONS

Studies relevant to phenotypes and treatment of wheezing illnesses in infants and preschool children were included.

RESULTS

Recurrent wheezing in preschool children is common and is frequently triggered by viral respiratory tract infections. Certain phenotypes may respond to treatments differently, depending on the risk factors identified. Inhaled corticosteroids, administered continuously or intermittently, reduce the risk of virus-induced wheezing episodes. The use of leukotriene modifying agents may have a role in wheezing episodes in a select group of preschool children. Early administration of azithromycin reduces the risk of severe lower respiratory tract illnesses in children. The effect of oral corticosteroids on wheezing episodes in young children varies by degree of episode severity.

CONCLUSION

Recurrent viral-induced wheezing illnesses has been the focus of many clinical trials, which now provide an increasingly robust evidence base for management. Additional research is needed to define optimal strategies, to best match therapies to specific phenotypes and endotypes, and will eventually begin to include therapies directed specifically at the viral triggers.