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Updated: Jun 21, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Development and validation of a clinical risk score nomogram for predicting voriconazole trough concentration above
Mengyuan Xie1,2, Manxue Jiang1,2, Jian Xu1,2
1Department of Pharmacy, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
Abstract:
The therapeutic range of voriconazole (VRC) is narrow, this study aimed to explore factors influencing VRC plasma concentrations > 5 mg/L and to construct a clinical risk score nomogram prediction model. Clinical data from 221 patients with VRC prophylaxis and treatment were retrospectively analyzed. The patients were randomly divided into a training cohort and a validation cohort at a 7:3 ratio. Univariate and binary logistic regression analysis was used to select independent risk factors for VRC plasma concentration above the high limit (5 mg/L). Four indicators including age, weight, CYP2C19 genotype, and albumin were selected to construct the nomogram prediction model. The area under the curve values of the training cohort and the validation cohort were 0.841 and 0.802, respectively. The decision curve analysis suggests that the nomogram model had good clinical applicability. In conclusion, the nomogram provides a reference for early screening and intervention in a high-risk population.
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