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Updated: Jun 3, 2025
Murine Model of Allergen Induced Asthma
Published on: May 14, 2012
Construction and validation of a predictive model for allergic rhinitis complicating children with bronchial asthma
Qi Zhang1, Fengqin Xu2, Fuzhe Chen2
1Department of Pediatric Respiratory Medicine, Anhui Provincial Children's Hospital, Hefei City, Anhui Province, China; zq_dr26@163.com.
Insights
Household smoking, elevated IgE, early antibiotic use, and inflammatory markers like CRP, WBC, and NLR are key risk factors for allergic rhinitis in children with asthma. A nomogram model aids in predicting this common complication.
Area of Science:
- Pediatric Allergy and Immunology
- Respiratory Medicine
- Clinical Prediction Modeling
Background:
- Allergic rhinitis frequently complicates bronchial asthma in children, impacting disease management and patient outcomes.
- Identifying predictive factors for allergic rhinitis is crucial for early intervention in pediatric asthma patients.
Purpose of the Study:
- To investigate factors associated with allergic rhinitis in children with bronchial asthma.
- To develop and validate a nomogram model for predicting allergic rhinitis in this population.
Main Methods:
- Retrospective analysis of 190 children with bronchial asthma, divided into training (133) and validation (57) cohorts.
- Multivariable logistic regression identified risk factors, including household smoking, IgE, early antibiotic use, C-reactive protein (CRP), white blood cell count (WBC), and neutrophils/lymphocytes ratio (NLR).
- A nomogram prediction model was constructed and validated, with C-indices of 0.919 (training) and 0.841 (validation).
Main Results:
- The incidence of allergic rhinitis complication was 32.63% (62/190 children).
- Risk factors identified included household smokers, elevated IgE, early antibiotic use, and higher CRP, WBC, and NLR levels.
- The nomogram model demonstrated good predictive accuracy and clinical utility in both cohorts.
Conclusions:
- Household smoking, IgE levels, early antibiotic exposure, and inflammatory markers (CRP, WBC, NLR) are significant risk factors for allergic rhinitis in children with asthma.
- The developed nomogram model serves as a valuable clinical tool for predicting allergic rhinitis in children diagnosed with bronchial asthma.
- This predictive model can facilitate targeted prevention and management strategies for comorbid allergic rhinitis in pediatric asthma patients.
Abstract:
This study aimed to investigate the factors influencing the complication of allergic rhinitis in children with bronchial asthma and to construct a nomogram model to predict the occurrence of allergic rhinitis. A total of 190 children with bronchial asthma admitted to our hospital from August 2020 to August 2024 were retrospectively analyzed. The children were randomly divided into the training cohort (133 cases) and validation cohort (57 cases) in a ratio of 7:3. The children in the modeling set were divided into an allergic rhinitis group (n=44) and a nonallergic rhinitis group (n=89) depending on the presence or absence of concomitant allergic rhinitis. A total of 62 cases in 190 children with bronchial asthma had complications with allergic rhinitis, with an incidence of 32.63%. In the training cohort, compared with the children in the nonallergic rhinitis group, percentage of smokers in the household, C-reactive protein (CRP), white blood cell count (WBC), and neutrophils/lymphocytes (NLR) were significantly higher in the allergic rhinitis group (P < 0.05). Multivariable logistic regression analysis showed that smokers in the household; IgE; early use of antibiotics; and elevated CRP, WBC, and NLR were all risk factors for the complication of allergic rhinitis in children with bronchial asthma (P < 0.05). A nomogram prediction model was constructed based on the above risk factors. The C-index of the nomogram was 0.919 (95% CI: 0.742-0.934) and 0.841 (95% CI: 0.773-0.902) for the training cohort and validation cohort, respectively. The Hosmer-Lemeshow test results of the training and validation cohorts were both P > 0.05, suggesting a good model fit. The results of DCA showed that the training and validation cohorts had good threshold probability and clinical net benefit. Smokers in the household, IgE, CRP, WBC, and NLR levels were all risk factors for the complication of allergic rhinitis in children with bronchial asthma. A nomogram model based on these risk factors may be a valuable clinical tool for predicting allergic rhinitis in children with bronchial asthma.
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