Creation and internal assessment of a comprehensive nomogram combining PIV, LDH, and FeNO to forecast inadequate asthma management in pediatric patients

By
Zhijian Zhan
Tianfu Xu
Saiping Huang
June 29, 2026

Frontiers In Pediatrics

Overview

This study developed and validated a nomogram integrating PIV, LDH, and FeNO to predict inadequate asthma management in pediatric patients. The model demonstrated superior predictive performance compared to individual biomarkers.

Background

Asthma is a prevalent chronic condition in children, often leading to poor control despite guideline-based treatments. Traditional assessment tools have limitations, necessitating the exploration of objective biomarkers for better risk stratification.

Data Highlights

Variable	Odds Ratio (OR)
PIV	1.008
LDH	1.043
FeNO	1.056
Asthma Duration	1.251
Vitamin D	0.891
FEV1% Predicted	0.953

Key Findings

Six independent predictors of poor asthma control were identified: PIV, LDH, FeNO, Vitamin D, asthma duration, and FEV1% predicted.
The combined model achieved an AUC of 0.886.
PIV, LDH, FeNO, and asthma duration were identified as risk factors for poor asthma control.
Vitamin D and FEV1% predicted were found to be protective factors.
The nomogram showed good calibration.

Clinical Implications

The integration of multiple biomarkers into a nomogram may enhance the identification of children at risk for poor asthma control. This approach supports personalized management strategies in pediatric asthma care.

Conclusion

The study presents a multidimensional model that effectively stratifies risk for poor asthma control in children, potentially aiding in tailored management strategies.