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Detecting a potential safety signal of antidepressants and type 2 diabetes: a pharmacovigilance-pharmacodynamic study.

ABSTRACT: AIMS:Recent data suggest that antidepressants are associated with incident diabetes but the possible pharmacological mechanism is still questioned. The aim of the present study was to evaluate antidepressant's risk for reporting diabetes using disproportionality analysis of the FDA adverse events spontaneous reporting system (FAERS) database and to investigate possible receptor/transporter mechanisms involved. METHODS:Data from 2004 to 2017 were analysed using OpenVigil2 and adjusted reporting odds ratio (aROR) for reporting diabetes was calculated for 22 antidepressants. Events included in the narrow scope of the SMQ 'hyperglycaemia/new-onset diabetes mellitus' were defined as cases and all the other events as non-cases. The pharmacodynamic profile was extracted using the PDSP and IUPHAR/BPS databases and the occupancy on receptors (serotonin, alpha adrenoreceptors, dopamine, muscarinic, histamine) and transporters (SERT, NET, DAT) was estimated. The relationship between aROR for diabetes and receptor occupancy was investigated with Pearson's correlation coefficient (r) and univariate linear regression. RESULTS:Six antidepressants were associated with diabetes: nortriptyline with aROR [95% CI] of 2.01 [1.41-2.87], doxepin 1.97 [1.31-2.97], imipramine 1.82 [1.09-3.06], sertraline 1.47 [1.29-1.68], mirtazapine 1.33 [1.04-1.69] and amitriptyline 1.31 [1.09-1.59]. Strong positive correlation coefficients between occupancy and aROR for diabetes were identified for the receptors M1 , M3 , M4 , M5 and H1 . CONCLUSION:Most of the tricyclic antidepressants, mirtazapine and sertraline seem to be associated with reporting diabetes in FAERS. Higher degrees of occupancy on muscarinic receptors and H1 may be a plausible pharmacological mechanism. Further clinical assessment and pharmacovigilance data is needed to validate this potential safety signal.

SUBMITTER: Siafis S

PROVIDER: S-EPMC6138477 | biostudies-other | 2018 Oct

REPOSITORIES: biostudies-other

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Detecting a potential safety signal of antidepressants and type 2 diabetes: a pharmacovigilance-pharmacodynamic study.

Siafis Spyridon S Papazisis Georgios G

British journal of clinical pharmacology 20180728 10

<h4>Aims</h4>Recent data suggest that antidepressants are associated with incident diabetes but the possible pharmacological mechanism is still questioned. The aim of the present study was to evaluate antidepressant's risk for reporting diabetes using disproportionality analysis of the FDA adverse events spontaneous reporting system (FAERS) database and to investigate possible receptor/transporter mechanisms involved.<h4>Methods</h4>Data from 2004 to 2017 were analysed using OpenVigil2 and adjus ...[more]

PMID: 29953643

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Project description:BackgroundAntidepressants-induced movement disorders are rare and imperfectly known adverse drug reactions. The risk may differ between different antidepressants and antidepressants' classes. The objective of this study was to assess the putative association of each antidepressant and antidepressants' classes with movement disorders.MethodsUsing VigiBase®, the WHO Pharmacovigilance database, disproportionality of movement disorders' reporting was assessed among adverse drug reactions related to any antidepressant, from January 1967 to February 2017, through a case/non-case design. The association between nine subtypes of movement disorders (akathisia, bruxism, dystonia, myoclonus, parkinsonism, restless legs syndrome, tardive dyskinesia, tics, tremor) and antidepressants was estimated through the calculation first of crude Reporting Odds Ratio (ROR), then adjusted ROR on four potential confounding factors: age, sex, drugs described as able to induce movement disorders, and drugs used to treat movement disorders.ResultsOut of the 14,270,446 reports included in VigiBase®, 1,027,405 (7.2%) contained at least one antidepressant, among whom 29,253 (2.8%) reported movement disorders. The female/male sex ratio was 2.15 and the mean age 50.9 ± 18.0 years. We found a significant increased ROR for antidepressants in general for all subtypes of movement disorders, with the highest association with bruxism (ROR 10.37, 95% CI 9.62-11.17) and the lowest with tics (ROR 1.49, 95% CI 1.38-1.60). When comparing each of the classes of antidepressants with the others, a significant association was observed for all subtypes of movement disorders except restless legs syndrome with serotonin reuptake inhibitors (SRIs) only. Among antidepressants, mirtazapine, vortioxetine, amoxapine, phenelzine, tryptophan and fluvoxamine were associated with the highest level to movement disorders and citalopram, paroxetine, duloxetine and mirtazapine were the most frequently associated with movement disorders. An association was also found with eight other antidepressants.ConclusionsA potential harmful association was found between movement disorders and use of the antidepressants mirtazapine, vortioxetine, amoxapine, phenelzine, tryptophan, fluvoxamine, citalopram, paroxetine, duloxetine, bupropion, clomipramine, escitalopram, fluoxetine, mianserin, sertraline, venlafaxine and vilazodone. Clinicians should beware of these adverse effects and monitor early warning signs carefully. However, this observational study must be interpreted as an exploratory analysis, and these results should be refined by future epidemiological studies.

Project description:In light of the favorable outcomes of few small, non-randomized clinical studies, the Food and Drug Administration (FDA) has issued an Emergency Use Authorization (EUA) to Hydroxychloroquine (HCQ) for hospitalized coronavirus disease 2019 (COVID-19) patients. In fact, subsequent clinical studies with COVID-19 and HCQ have reported limited efficacy and poor clinical benefits. Unfortunately, a robust clinical trial for its effectiveness is not feasible at this emergency. Additionally, HCQ was suspected of causing cardiovascular adverse reactions (CV-AEs), but it has never been directly investigated. The objective of this pharmacovigilance analysis was to determine and characterize HCQ-associated cardiovascular adverse events (CV-AEs). We performed a disproportionality analysis of HCQ-associated CV-AEs using the FDA adverse event reporting system (FAERS) database. The FAERS database, comprising more than 11,901,836 datasets and 10,668,655 patient records with drug-adverse reactions, was analyzed. The disproportionality analysis was used to calculate the reporting odds ratios (ROR) with 95% confidence intervals (CI) to predict HCQ-associated CV-AEs. HCQ was associated with higher reporting of right ventricular hypertrophy (ROR: 6.68; 95% CI: 4.02 to 11.17), left ventricular hypertrophy (ROR: 3.81; 95% CI: 2.57 to 5.66), diastolic dysfunction (ROR: 3.54; 95% CI: 2.19 to 5.71), pericarditis (ROR: 3.09; 95% CI: 2.27 to 4.23), torsades de pointes (TdP) (ROR: 3.05; 95% CI: 2.30 to 4.10), congestive cardiomyopathy (ROR: 2.98; 95% CI: 2.01 to 4.42), ejection fraction decreased (ROR: 2.41; 95% CI: 1.80 to 3.22), right ventricular failure (ROR: 2.40; 95% CI: 1.64 to 3.50), atrioventricular block complete (ROR: 2.30; 95% CI: 1.55 to 3.41) and QT prolongation (ROR: 2.09; 95% CI: 1.74 to 2.52). QT prolongation and TdP are most relevant to the COVID-19 treatment regimen of high doses for a comparatively short period and represent the most common HCQ-associated AEs. The patients receiving HCQ are at higher risk of various cardiac AEs, including QT prolongation and TdP. These findings highlight the urgent need for prospective, randomized, controlled studies to assess the risk/benefit ratio of HCQ in the COVID-19 setting before its widespread adoption as therapy.

Project description:BackgroundPharmacovigilance programmes monitor and help ensuring the safe use of medicines which is critical to the success of public health programmes. The commonest method used for discovering previously unknown safety risks is spontaneous notifications. In this study we examine the use of data mining algorithms to identify signals from adverse events reported in a phase IIIb/IV clinical trial evaluating the efficacy and safety of several Artemisinin-based combination therapies (ACTs) for treatment of uncomplicated malaria in African children.MethodsWe used paediatric safety data from a multi-site, multi-country clinical study conducted in seven African countries (Burkina Faso, Gabon, Nigeria, Rwanda, Uganda, Zambia, and Mozambique). Each site compared three out of four ACTs, namely amodiaquine-artesunate (ASAQ), dihydroartemisinin-piperaquine (DHAPQ), artemether-lumefantrine (AL) or chlorproguanil/dapsone and artesunate (CD+A). We examine two pharmacovigilance signal detection methods, namely proportional reporting ratio and Bayesian Confidence Propagation Neural Network on the clinical safety dataset.ResultsAmong the 4,116 children (6-59 months old) enrolled and followed up for 28 days post treatment, a total of 6,238 adverse events were reported resulting into 346 drug-event combinations. Nine signals were generated both by proportional reporting ratio and Bayesian Confidence Propagation Neural Network. A review of the manufacturer package leaflets, an online Multi-Drug Symptom/Interaction Checker (DoubleCheckMD) and further by therapeutic area experts reduced the number of signals to five. The ranking of some drug-adverse reaction pairs on the basis of their signal index differed between the two methods.ConclusionsOur two data mining methods were equally able to generate suspected signals using the pooled safety data from a phase IIIb/IV clinical trial. This analysis demonstrated the possibility of utilising clinical studies safety data for key pharmacovigilance activities like signal detection and evaluation. This approach can be applied to complement the spontaneous reporting systems which are limited by under reporting.

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Dataset Information

Detecting a potential safety signal of antidepressants and type 2 diabetes: a pharmacovigilance-pharmacodynamic study.

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Detecting a potential safety signal of antidepressants and type 2 diabetes: a pharmacovigilance-pharmacodynamic study.

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