Abstract
BACKGROUND: Pediatric asthma is a chronic and heterogeneous respiratory disease that poses considerable challenges in predicting exacerbations and long-term outcomes. This study aimed to enhance prognostic prediction for pediatric asthma by integrating serological markers with pulmonary function parameters. METHODS: A retrospective analysis was conducted involving 318 pediatric asthma patients from one hospital, with external validation performed on an additional cohort of 283 patients from another institution. Serological markers, including white blood cell (WBC) count, eosinophil percentage, interleukins, 14-3-3β protein, and total immunoglobulin E (IgE), were measured alongside pulmonary function indicators such as forced expiratory volume in one second (FEV1) and the FEV1/forced vital capacity (FVC) ratio. Statistical analyses included correlation testing, logistic regression analysis, and receiver operating characteristic (ROC) curve analysis to develop and validate the prognostic model. RESULTS: Elevated WBC count, eosinophil percentage, 14-3-3β protein, and total IgE levels were significantly associated with poorer prognosis. Among interleukin profiles, increased interleukin-4 (IL-4) and interleukin-7 (IL-7) levels, along with reduced interleukin-10 (IL-10), were linked to unfavorable outcomes. In contrast, higher FEV1 and FVC values correlated with better outcomes. The integrated predictive model demonstrated strong predictive performance, with an area under the curve (AUC) of 0.818 in the modeling cohort and 0.874 in the validation cohort. CONCLUSION: The integration of serological biomarkers and pulmonary function indices provides a robust framework for predicting prognosis in pediatric asthma, supporting the development of individualized management strategies.