Anticonvulsant and antipsychotic medications in the pharmacotherapy of panic disorder: a structured review

Antipsychotic agents in anxiety disorders: An umbrella review

BACKGROUND

Although not approved for the treatment of anxiety disorders (except trifluoperazine) there is ongoing off-label, unapproved use of first-generation antipsychotics (FGAs) and second-generation antipsychotics (SGAs) for anxiety disorders. There have been systematic reviews and meta-analyses on the use of antipsychotics in anxiety disorders, most of which focused on SGAs.

OBJECTIVE

The specific aims of this umbrella review are to: (1) Evaluate the evidence of efficacy of FGAs and SGAs in anxiety disorders as an adjunctive treatment to traditional antidepressant treatments and other nonantipsychotic medications; (2) Compare monotherapy with antipsychotics to first-line treatments for anxiety disorders in terms of effectiveness, risks, and side effects. The review protocol is registered on PROSPERO (CRD42021237436).

METHODS

An initial search was undertaken to identify systematic reviews and meta-analyses from inception until 2020, with an updated search completed August 2021 and January 2023. The searches were conducted in PubMed, MEDLINE (Ovid), EMBASE (Ovid), APA PsycInfo (Ovid), CINAHL Complete (EBSCOhost), and the Cochrane Library through hand searches of references of included articles. Review quality was measured using the AMSTAR-2 (A MeaSurement Tool to Assess Systematic Reviews) scale.

RESULTS

The original and updated searches yielded 1796 and 3744 articles respectively, of which 45 were eligible. After final review, 25 systematic reviews and meta-analyses were included in the analysis. Most of the systematic reviews and meta-analyses were deemed low-quality through AMSTAR-2 with only one review being deemed high-quality. In evaluating the monotherapies with antipsychotics compared with first-line treatments for anxiety disorder there was insufficient evidence due to flawed study designs (such as problems with randomization) and small sample sizes within studies. There was limited evidence suggesting efficacy of antipsychotic agents in anxiety disorders other than quetiapine in generalized anxiety disorder (GAD).

CONCLUSIONS

This umbrella review indicates a lack of high-quality studies of antipsychotics in anxiety disorders outside of the use of quetiapine in GAD. Although potentially effective for anxiety disorders, FGAs and SGAs may have risks and side effects that outweigh their efficacy, although there were limited data. Further long-term and larger-scale studies of antipsychotics in anxiety disorders are needed.

Network pharmacology study on the mechanism of Qiangzhifang in the treatment of panic disorder

Background

Panic disorder (PD) is a kind of mental illness characterized by the symptom of recurring panic attacks. Qiangzhifang (QZF) is a novel decoction developed by Professor Zhaojun Yan based on a unique system of syndrome differentiation and clinical experience. It has achieved remarkable results after long-term clinical practice, but its mechanism of action is still unclear. This study aims to use network pharmacology and molecular docking to explore the mechanism of QZF in the treatment of PD.

Methods

We used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), a literature search, and Encyclopedia of Traditional Chinese Medicine (ETCM) to find active ingredients and targets of QZF. We searched for PD targets in GeneCards, Online Mendelian Inheritance in Man (OMIM), the Comparative Toxicogenomics Database (CTD), and DrugBank. We established a PD target database, constructed a protein-protein interaction (PPI) network, and performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis in order to screen possible pathways of action and analyze the mechanism.

Results

This study identified 84 effective components of QZF, 691 potential targets, 357 PD targets, and 97 intersectional targets. Enrichment analysis using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) showed that QZF was associated with 118 biological processes (BPs), 18 cellular components (CCs), 35 molecular functions (MFs) [false discovery rate (FDR) <0.01], and 62 pathways (FDR <0.01). QZF mainly acts on its targets AKT1, FOS, and APP through active ingredients such as quercetin, β-sitosterol, 4-(4'-hydroxybenzyloxy)benzyl methyl ether, harmine, 1,7-dimethoxyxanthone, and 1-hydroxy-3,7-dimethoxyxanthone to regulate serotonin, gamma-aminobutyric acid (GABA), cyclic adenosine monophosphate (cAMP), and other signal pathways to treat PD.

Conclusions

Through network pharmacology and molecular docking technology, we predicted the possible mechanism of QZF in the treatment of PD, revealed the interaction targets and potential value of QZF, and provided a basis for its clinical application.