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Assessing Pharmacokinetic Correlates of Escitalopram-Related Adverse Drug Reactions
Maxim Kuzin1,2, Ekkehard Haen3,4,5, Nazar Kuzo6
1Clienia Schloessli, Private Psychiatric Hospital and Academic Teaching Hospital of the University of Zurich, Oetwil am See/Zurich, Switzerland.
Background:
To assess the pharmacokinetic correlates of reported adverse drug reactions (ADRs) under antidepressant treatment with escitalopram (ESC) using a large therapeutic drug monitoring database.
Methods:
A large naturalistic sample of inpatients and outpatients prescribed ESC was analyzed. ADRs were classified using the Udvalg for Kliniske Undersogelser side effect rating scale. We compared ESC-treated patients with (n = 35) and without ADRs (n = 273) using ESC plasma concentrations as the primary outcome. We also compared ADR rates in the 2 groups based on 2 cut-off ESC levels reflecting the recommended upper thresholds of the therapeutic reference range of 80 ng/mL, suggested by the consensus therapeutic drug monitoring guidelines, and 40 ng/mL, based on recent meta-analysis data. The effects of age, sex, smoking, daily ESC dose, plasma concentrations, and concentrations corrected for daily dose were included in a binary logistic regression model to predict ADRs.
Results:
No differences in clinical, demographic, or pharmacokinetic parameters were observed between patients with and without ADRs ( P > 0.05). Patients with ESC-related ADRs were more frequently diagnosed with psychotic disorders than those without (25% vs. 7.1%, P = 0.004). None of the variables was associated with ADR risk. Overall, ADR rates were not significantly different in patients above versus below thresholds of ESC concentrations (ESC concentrations >40 [n = 59] vs. ≤40 ng/mL [n = 249] and >80 [n = 8] vs. ≤80 ng/mL [n = 300]; P = 0.56 and P = 1.0, respectively).
Conclusions:
No distinct pharmacokinetic patterns underlying ESC-associated ADRs were observed. Further studies with more specific assessments of ADRs in larger cohorts are required to better identify potential underlying patterns.
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