Quetiapine- and Valproate-Associated Neutropenia and Thrombocytopenia After Lamotrigine-Induced Steven-Johnson Syndrome

Chang, Li-Ren; Chang, Hung-Chieh Wu; Lin, Yu‐Hsuan

doi:10.1097/jcp.0b013e31823f87e5

Cited by 6 publications

(5 citation statements)

References 14 publications

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“…In addition to delirium, neutropenia appeared in our predictions for valproic acid. Likewise, neutropenia following valproic acid exposure was also observed in other studies [ 54 – 56 ]. The FDA drug label does not specify neutropenia as an adverse reaction for valproic acid, but leukopenia is labeled.…”

Section: Discussionsupporting

confidence: 81%

Drug voyager: a computational platform for exploring unintended drug action

Ahn

Lee

et al. 2017

BMC Bioinformatics

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BackgroundThe dominant paradigm in understanding drug action focuses on the intended therapeutic effects and frequent adverse reactions. However, this approach may limit opportunities to grasp unintended drug actions, which can open up channels to repurpose existing drugs and identify rare adverse drug reactions. Advances in systems biology can be exploited to comprehensively understand pharmacodynamic actions, although proper frameworks to represent drug actions are still lacking.ResultsWe suggest a novel platform to construct a drug-specific pathway in which a molecular-level mechanism of action is formulated based on pharmacologic, pharmacogenomic, transcriptomic, and phenotypic data related to drug response (http://databio.gachon.ac.kr/tools/). In this platform, an adoption of three conceptual levels imitating drug perturbation allows these pathways to be realistically rendered in comparison to those of other models. Furthermore, we propose a new method that exploits functional features of the drug-specific pathways to predict new indications as well as adverse reactions. For therapeutic uses, our predictions significantly overlapped with clinical trials and an up-to-date drug-disease association database. Also, our method outperforms existing methods with regard to classification of active compounds for cancers. For adverse reactions, our predictions were significantly enriched in an independent database derived from the Food and Drug Administration (FDA) Adverse Event Reporting System and meaningfully cover an Adverse Reaction Database provided by Health Canada. Lastly, we discuss several predictions for both therapeutic indications and side-effects through the published literature.ConclusionsOur study addresses how we can computationally represent drug-signaling pathways to understand unintended drug actions and to facilitate drug discovery and screening.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1558-3) contains supplementary material, which is available to authorized users.

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Section: Discussionsupporting

confidence: 81%

Drug voyager: a computational platform for exploring unintended drug action

Ahn

Lee

et al. 2017

BMC Bioinformatics

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“…Incidence of leukopenia and neutropenia related to LTG is known to be more frequent, but the exact estimated number has not been reported. Studies from psychiatric patients showed that combination treatment of ASDs and antipsychotics increased the risk of neutropenia and/or leukopenia …”

Section: Discussionmentioning

confidence: 99%

Analysis of antiseizure drug‐related adverse reactions from the electronic health record using the common data model

Choi

Kim

et al. 2020

Epilepsia

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Objective: Antiseizure drugs (ASDs) are known to cause a wide range of adverse drug reactions (ADRs). Recently, electronic health care data using the common data model (CDM) have been introduced and commonly adopted in pharmacovigilance research. We aimed to analyze ASD-related ADRs using CDM and to assess the feasibility of CDM analysis in monitoring ADR in a single tertiary hospital. Methods: We selected five ASDs: oxcarbazepine (OXC), lamotrigine (LTG), levetiracetam (LEV), valproic acid (VPA), and topiramate (TPM). Patients diagnosed with epilepsy and exposed to monotherapy with one of the ASDs before age 18 years were included. We measured four ADR outcomes: (1) hematologic abnormality, (2) hyponatremia, (3) elevation of liver enzymes, and (4) subclinical hypothyroidism. We performed a subgroup analysis to exclude the effects of concomitant medications. Results: From the database, 1344 patients were included for the study. Of the 1344 patients, 436 were receiving OXC, 293 were receiving LTG, 275 were receiving LEV, 180 were receiving VPA, and 160 were receiving TPM. Thrombocytopenia developed in 14.1% of patients taking VPA. Hyponatremia occurred in 10.5% of patients taking OXC. Variable ranges of liver enzyme elevation were detected in 19.3% of patients taking VPA. Subclinical hypothyroidism occurred in approximately 21.5% to 28% of patients with ASD monotherapy, which did not significantly differ according to the type of ASD. In a subgroup analysis, we observed similar ADR tendencies, but with less thrombocytopenia in the TPM group. Significance: The incidence and trends of ADRs that were evaluated by CDM were similar to the previous literature. CDM can be a useful tool for analyzing ASDrelated ADRs in a multicenter study. The strengths and limitations of CDM should be carefully addressed. K E Y W O R D Sadverse drug reaction, antiseizure drugs, common data model, epilepsy, pharmacovigilance | 611 CHOI et al.

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“…The authors postulate that a pharmacokinetic interaction in which valproic acid raises the plasma concentrations of quetiapine is to blame for the increased incidence of leukopenia and thrombocytopenia when they are used together. Other reports of neutropenia, leukopenia and thrombocytopenia being blamed on the addition of quetiapine to a drug regimen including valproic acid have been published,[31–34] including a case where white blood count and neutrophil count were normal for several weeks prior to addition of quetiapine but fell sharply on its addition [35]…”

Section: Clinical Reports Of Adverse Drug Reactions Possibly Caused Bmentioning

confidence: 99%

Interactions between valproic acid and quetiapine/olanzapine in the treatment of bipolar disorder and the role of therapeutic drug monitoring

Vella

Mifsud

2014

Journal of Pharmacy and Pharmacology

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Objectives The anticonvulsant valproic acid and the atypical antipsychotics olanzapine and quetiapine provide synergistic mood-stabilising, antidepressant and antipsychotic activities in the treatment of bipolar and schizoaffective disorders. Existing literature shows that pharmacokinetic and pharmacodynamics drug-drug interactions (DDIs) possibly occur with the use of such a combination. Clinical reports of a possible interaction between the drugs leading to an increased risk of adverse drug reactions have also emerged. The main objective of this paper is to review the incidence of DDIs between the anticonvulsant and the antipsychotics, to postulate the possible mechanisms of the interaction and to establish whether certain target populations are at an increased susceptibility to such interactions. The usefulness of therapeutic drug monitoring (TDM) of the antipsychotics to monitor for an interaction was also assessed. A systematic database search was carried out using the search engine provided by PubMed using the following key words: olanzapine, quetiapine, valproic acid, pharmacokinetic drugdrug interaction, bipolar disorder, therapeutic drug monitoring. Key findings Evidence of a possible clinically relevant DDI between valproic acid and both antipsychotics has been uncovered. A possible mechanism for the interactions has been postulated, and the importance of TDM has been discussed. Summary Further research is required to determine whether DDIs occur with the concurrent use of valproic acid and olanzapine or quetiapine, and to investigate the potential of TDM as a clinical tool in improving pharmacotherapy and preventing toxicity.

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Quetiapine- and Valproate-Associated Neutropenia and Thrombocytopenia After Lamotrigine-Induced Steven-Johnson Syndrome

Cited by 6 publications

References 14 publications

Drug voyager: a computational platform for exploring unintended drug action

Drug voyager: a computational platform for exploring unintended drug action

Analysis of antiseizure drug‐related adverse reactions from the electronic health record using the common data model

Interactions between valproic acid and quetiapine/olanzapine in the treatment of bipolar disorder and the role of therapeutic drug monitoring

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