Evidence map›Paper›PMID 42339471›Full record

ArticleJournal of asthma and allergy2026

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

Jiangjiao Qin, Sha Liu, Ying Lin, Xia Wang, Jing Zhao, Fangjun Liu

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Article in Journal of asthma and allergy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Jiangjiao QinDepartment of Pulmonary Function, Children's Hospital of Chongqing Medical University, Chongqing, People's Republic of China.
Sha LiuDepartment of Pulmonary Function, Children's Hospital of Chongqing Medical University, Chongqing, People's Republic of China.
Ying LinDepartment of Pulmonary Function, Children's Hospital of Chongqing Medical University, Chongqing, People's Republic of China.
Xia WangDepartment of Pulmonary Function, Children's Hospital of Chongqing Medical University, Chongqing, People's Republic of China.
Jing ZhaoDepartment of Pulmonary Function, Children's Hospital of Chongqing Medical University, Chongqing, People's Republic of China.
Fangjun LiuDepartment of Pulmonary Function, Children's Hospital of Chongqing Medical University, Chongqing, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: 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.

Indexed as

exhaled nitric oxidemethacholine challenge testnomogramtidal breathing

Identifiers

PMID42339471
PMCPMC13284878

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.