Factors to influence the accuracy of albumin adjusted free valproic acid concentration

Predictors of valproic acid steady-state serum levels in adult and pediatric psychiatric inpatients: a comparative analysis

RATIONALE

Valproic acid (VPA) is commonly used as a second-line mood stabilizer or augmentative agent in severe mental illnesses. However, population pharmacokinetic studies specific to psychiatric populations are limited, and clinical predictors for the precision application of VPA remain undefined.

OBJECTIVES

To identify steady-state serum VPA level predictors in pediatric/adolescent and adult psychiatric inpatients.

METHODS

We analyzed data from 634 patients and 1,068 steady-state therapeutic drug monitoring (TDM) data points recorded from 2015 to 2021. Steady-state VPA levels were obtained after tapering during each hospitalization episode. Electronic patient records were screened for routine clinical parameters and co-medication. Generalized additive mixed models were employed to identify independent predictors.

RESULTS

Most TDM episodes involved patients with psychotic disorders, including schizophrenia (29.2%) and schizoaffective disorder (17.3%). Polypharmacy was common, with the most frequent combinations being VPA + quetiapine and VPA + promethazine. Age was significantly associated with VPA levels, with pediatric/adolescent patients (< 18 years) demonstrating higher dose-adjusted serum levels of VPA (β = 7.6±2.34, p < 0.001) after accounting for BMI. Women tended to have higher adjusted VPA serum levels than men (β = 5.08±1.62, p < 0.001). The formulation of VPA (Immediate-release vs. extended-release) showed no association with VPA levels. Co-administration of diazepam exhibited a dose-dependent decrease in VPA levels (F = 15.7, p < 0.001), suggesting a potential pharmacokinetic interaction.

CONCLUSIONS

This study highlights the utility of population-specific pharmacokinetic data for VPA in psychiatric populations. Age, gender, and co-administration of diazepam were identified as predictors of VPA levels. Further research is warranted to establish additional predictors and optimize the precision application of VPA in psychiatric patients.

Valproic acid monitoring: Serum prediction using a machine learning framework from multicenter real-world data

BACKGROUND

Our study employs machine learning to predict serum valproic acid (VPA) concentrations, aiming to contribute to the development of non-invasive assays for therapeutic drug monitoring.

METHODS

Medical records from 2002 to 2019 were obtained from the Taiwan Chang Gung Research Database. Using various machine learning algorithms, we developed predictive models to classify serum VPA concentrations into two categories (1-50 μg/ml or 51-100 μg/ml) and predicted the exact concentration value. The models were trained on 5142 samples and tested on 644 independent samples. Accuracy was the main metric used to evaluate model performance, with a tolerance of 20 μg/ml for continuous variables. Furthermore, we identified important features and developed simplified models with fewer features.

RESULTS

The models achieved an average accuracy of 0.80-0.86 for binary outcomes and 0.72-0.88 for continuous outcome. Ten top features associated with higher serum VPA levels included higher VPA last and daily doses, bipolar disorder or schizophrenia spectrum disorder diagnoses, elevated levels of serum albumin, calcium, and creatinine, low platelet count, low percentage of segmented white blood cells, and low red cell distribution width-coefficient of variation. The simplified models had an average accuracy of 0.82-0.86 for binary outcome and 0.70-0.86 for continuous outcome.

LIMITATIONS

The study's predictive model lacked external test data from outside the hospital for validation.

CONCLUSIONS

Machine learning models have the potential to integrate real-world data and predict VPA concentrations, providing a promising tool for reducing the need for frequent monitoring of serum levels in clinical practice.

A novel method for predicting the unbound valproic acid concentration

In this study, we constructed a prediction formula for unbound valproic acid (VPA) concentration that was more accurate and widely applicable than previously reported formulae. A total of 136 datasets from 75 patients were analyzed retrospectively. The median of free fraction of VPA was 0.16 (interquartile range: 0.07; range: 0.07-0.45). The parameter that combined total VPA concentration (C_tVPA) and serum albumin (SA), (C_tVPA [μM] - 2 × SA [μM]), was significantly related to the free fraction of VPA (r = 0.76, p < 0.001). We constructed a combined parameter-based prediction formula for unbound VPA concentration. Analysis using external datasets from patients without severe renal failure showed that the prediction errors of the unbound VPA concentration were lower than those of previously reported formulae. Although the previous formulae showed large prediction errors, especially in the specific range of C_tVPA values, the constructed formula showed a weak trend with C_tVPA or SA. The formula based on (C_tVPA [μM] - 2 × SA [μM]) had high prediction accuracy and wide applicability in predicting the unbound VPA concentration in patients without severe renal failure.

Clinical Pharmacokinetic Monitoring of Free Valproic Acid Levels: A Systematic Review

BACKGROUND

Current guidelines recommend therapeutic drug monitoring as a critical component of valproic acid (VPA) therapy. Due to high protein binding, the active unbound (free) portion of VPA can be misrepresented by total VPA serum levels in certain clinical scenarios. Monitoring free VPA serum levels may be warranted when assessing the clinical response to VPA therapy.

OBJECTIVES

The aims were to conduct a systematic review to identify a therapeutic range for free VPA serum levels; to explore the correlation of free VPA serum levels with clinical toxicity and therapeutic benefit; and to examine predictors of discordance between free and total VPA levels.

METHODS

Medline, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL), PsycINFO, BIOSIS Previews, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) were searched from the time of database inception to June 20, 2021. Randomized controlled trials and observational studies that evaluated any patient receiving VPA with free VPA level monitoring were included.

RESULTS

Of 189 citations, we identified 27 relevant studies, which included 14 observational studies, two case series, and 11 case reports. Three studies provided a therapeutic range for free VPA levels between 20 and 410 μmol/L. Two studies suggested the occurrence of hyperammonemia and thrombocytopenia at free VPA serum levels above 60 µmol/L and 103.3 µmol/L, respectively. Two studies suggested an upper limit for neurotoxicity at free VPA serum levels of 70 µmol/L and 207.9 µmol/L. Hypoalbuminemia was identified as a predictor of therapeutic discordance.

CONCLUSIONS

This review demonstrates a paucity of data informing the clinical utility of free VPA serum levels. Further high-quality trials are needed to validate an optimal therapeutic range for free VPA levels.