A risk prediction model for serum valproic acid concentrations exceeding the safety threshold

doi:10.19803/j.1672-8629.20260451

Abstract

Abstract: Objective To establish a nomogram model to identify independent factors associated with serum VPA concentrations that exceed the safety threshold so as to provide a reference for safe clinical use of VPA. Methods The patients were divided into two groups based on serum VPA concentration: a therapeutic range group (50-100 μg·mL^-1) and a group exceeding the safety threshold (>100 μg·mL^-1). R4.3.0 software was used to establish a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the discriminative ability of the model while the Hosmer-Lemeshow goodness-of-fit test was used to assess the accuracy of prediction. Results A total of 813 patients were enrolled, including 699 in the VPA therapeutic range group and 114 in the group exceeding the safety threshold. Lasso regression identified four top predictors: gender, body weight, body mass index, and administration routes. Binary logistic regression analysis found that body weight (OR=0.985) and administration routes (OR=5.880) were independent risk and protective factors, respectively, for maintaining serum VPA concentrations within the therapeutic range. The nomogram model was moderately accurate for predicting patients exceeding the safety threshold, with an ROC AUC of 0.705 (95%CI: 0.654-0.757), a sensitivity of 78.95%, and a specificity of 55.94%. The Hosmer-Lemeshow test indicated good model fit (χ²=14.144, P=0.078). Decision curve analysis showed that the nomogram model provided a good net benefit in predicting whether serum VPA concentrations were within the therapeutic range across a range of high-risk threshold probabilities. Conclusion Body weight and administration routes are independent risk factors associated with serum VPA concentrations exceeding the safety threshold. The nomogram model can effectively estimate the risk of elevated serum VPA concentrations.

Key words: Valproic Acid (VPA), Serum Drug Concentration, Exceed the Safety Threshold, Prediction, Body Weight, Administration Route, Therapeutic Drug Monitoring (TDM)

CLC Number:

R971
R994.11

Feng Jie, Zhang Huilan, Liu Lei, Wu Wanyan, Li Yanju, Li Hongjian. A risk prediction model for serum valproic acid concentrations exceeding the safety threshold[J]. Chinese Journal of Pharmacovigilance, 2026, 23(9): 1028-1033.

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https://zgywjj.magtechjournal.com/EN/Y2026/V23/I9/1028

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