Development and Internal Evaluation of a Clinical-Physiological Model for Predicting Methacholine-Defined Airway Hyperresponsiveness in Children Aged 0–3 Years

Jiangjiao Qin,1,2 Sha Liu,1,2 Ying Lin,1,2 Xia Wang,1,2 Jing Zhao,1,2 Fangjun Liu1,2 1Department of Pulmonary Function, Children’s Hospital of Chongqing Medical University, Chongqing, People’s Republic of China; 2National Clinical Research Center for Children and Adolescents’ Health and Diseases; Ministry of Education Key Laboratory of Child Development and Disorders; Chongqing Key Laboratory of Pediatric Metabolism and Inflammatory Diseases, Children’s Hospital of Chongqing Medical University, Chongqing, People’s Republic of ChinaCorrespondence: Fangjun Liu, Department of Pulmonary Function, Children’s Hospital of Chongqing Medical University, Chongqing, People’s Republic of China, Tel +86 15215048191, Fax +86 23-63631510, Email [email protected]: Assessing airway hyperresponsiveness (AHR) in children aged 0– 3 years is crucial for early asthma diagnosis but is clinically challenging due to the safety risks and technical complexity of the methacholine challenge test (MCT). This study aimed to develop and internally evaluate a non-invasive, multidimensional nomogram to predict current methacholine-defined AHR in children aged 0– 3 years with suspected asthma.Patients and Methods: We conducted a retrospective cohort study of children aged 0– 3 years with suspected asthma who underwent same-day tidal breathing pulmonary function testing, fractional exhaled nitric oxide (FeNO) measurement, and MCT. Clinical symptoms and atopic history were extracted from electronic medical records. Multivariable logistic regression was used to identify independent predictors of AHR. The model was internally evaluated using a single 70/30 random split into training and evaluation cohorts. Model performance was assessed by discrimination, calibration, and decision curve analysis and compared with machine-learning approaches.Results: Seven independent predictors were identified: family history of asthma (OR = 3.90), presence of wheeze (OR = 3.85), history of allergy (OR = 2.34), history of rhinitis (OR = 1.69), FeNO (OR = 1.03), age (OR = 0.96), and TPTEF/TE (OR = 0.97). The model achieved an AUC of 0.81 (95% CI: 0.77– 0.85) in the training cohort and 0.76 (95% CI: 0.69– 0.84) in the evaluation cohort. At the optimal cutoff, the PPV and NPV were 0.89 and 0.39, respectively, in the evaluation cohort. SHAP analysis identified family history of asthma, wheeze, and FeNO as the most influential predictors.Conclusion: We developed a clinical-physiological nomogram for predicting methacholine-defined AHR in children aged 0– 3 years. It serves as an adjunctive tool in tertiary care to identify patients with a high probability of AHR.Keywords: methacholine challenge test, tidal breathing, exhaled nitric oxide, nomogram