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Age-stratified nomogram development and validation for predicting voriconazole trough concentrations above safety

Na An1, Yu Han1, Chenhong Jia1

  • 1Department of Pharmacy, Hebei Children's Hospital, Hebei Provincial Clinical Research Center for Child Health and Disease, 133 Jianhua South Street, Shijiazhuang, Hebei Province, 050031, People's Republic of China.

European Journal of Clinical Pharmacology
|April 29, 2026
PubMed

Insights

This study developed an age-stratified nomogram to predict high voriconazole (VRC) levels in pediatric hematologic malignancy (HM) patients. The model aids in early risk identification and may reduce therapeutic drug monitoring frequency.

Area of Science:

  • Pharmacology
  • Pediatric Oncology
  • Clinical Pharmacy

Background:

  • Voriconazole (VRC) is crucial for treating invasive fungal infections in pediatric patients with hematologic malignancies (HM).
  • Therapeutic drug monitoring (TDM) is essential for optimizing VRC dosage, but predicting supratherapeutic concentrations remains challenging.
  • Age-specific factors may influence VRC pharmacokinetics and safety thresholds in pediatric HM populations.

Purpose of the Study:

  • To develop and validate an age-stratified nomogram for predicting the risk of VRC trough concentrations exceeding the safety threshold.
  • To identify key clinical and laboratory factors associated with VRC overexposure in pediatric HM patients.
  • To assess the clinical utility of the predictive model in guiding TDM strategies.

Main Methods:

  • Retrospective enrollment of pediatric HM patients receiving VRC with TDM.
  • Age stratification (≥ and < 11 years) and random assignment to training/testing cohorts (6:4 ratio).
  • Least Absolute Shrinkage and Selection Operator (LASSO) regression for variable screening and multivariate logistic regression for model development.
  • Area Under the Receiver Operating Characteristic Curve (AUC) and decision curve analysis for performance evaluation.

Main Results:

  • C-reactive protein, albumin, and neutropenia were predictors in patients ≥ 11 years.
  • Blood urea nitrogen and direct bilirubin were predictors in patients < 11 years.
  • Test cohort AUCs were 0.835 (≥ 11 years) and 0.814 (< 11 years).
  • Models achieved high sensitivity (≥ 95%) with specificities of 43.75% and 29.76%, potentially reducing TDM frequency by 33.70% and 23.41% respectively.
  • Decision curve analysis demonstrated superior clinical net benefit compared to 'treat-all' or 'treat-none' strategies.

Conclusions:

  • The developed age-stratified prediction model effectively identifies pediatric HM patients at high risk of VRC overexposure.
  • The model exhibits good discrimination and clinical utility.
  • This tool can facilitate early risk warnings and potentially optimize TDM in pediatric HM patients.
Abstract

Keywords:
Hematologic MalignancyNomogramPediatricTherapeutic concentrationVoriconazole

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