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Detecting drug interactions from adverse-event reports: interaction between paroxetine and pravastatin increases blood glucose levels.

ABSTRACT: The lipid-lowering agent pravastatin and the antidepressant paroxetine are among the most widely prescribed drugs in the world. Unexpected interactions between them could have important public health implications. We mined the US Food and Drug Administration's (FDA's) Adverse Event Reporting System (AERS) for side-effect profiles involving glucose homeostasis and found a surprisingly strong signal for comedication with pravastatin and paroxetine. We retrospectively evaluated changes in blood glucose in 104 patients with diabetes and 135 without diabetes who had received comedication with these two drugs, using data in electronic medical record (EMR) systems of three geographically distinct sites. We assessed the mean random blood glucose levels before and after treatment with the drugs. We found that pravastatin and paroxetine, when administered together, had a synergistic effect on blood glucose. The average increase was 19 mg/dl (1.0 mmol/l) overall, and in those with diabetes it was 48 mg/dl (2.7 mmol/l). In contrast, neither drug administered singly was associated with such changes in glucose levels. An increase in glucose levels is not a general effect of combined therapy with selective serotonin reuptake inhibitors (SSRIs) and statins.

SUBMITTER: Tatonetti NP

PROVIDER: S-EPMC3216673 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature

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Detecting drug interactions from adverse-event reports: interaction between paroxetine and pravastatin increases blood glucose levels.

Tatonetti N P NP Denny J C JC Murphy S N SN Fernald G H GH Krishnan G G Castro V V Yue P P Tsao P S PS Kohane I I Roden D M DM Altman R B RB

Clinical pharmacology and therapeutics 20110525 1

The lipid-lowering agent pravastatin and the antidepressant paroxetine are among the most widely prescribed drugs in the world. Unexpected interactions between them could have important public health implications. We mined the US Food and Drug Administration's (FDA's) Adverse Event Reporting System (AERS) for side-effect profiles involving glucose homeostasis and found a surprisingly strong signal for comedication with pravastatin and paroxetine. We retrospectively evaluated changes in blood glu ...[more]

PMID: 21613990

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Project description:BackgroundAccurately characterizing a drug's safety profile is essential. Trial harm and tolerability assessments rely, in part, on participants' reports of medical histories, adverse events (AEs), and concomitant medications. Optimal methods for questioning participants are unclear, but different methods giving different results can undermine meta-analyses. This study compared methods for eliciting such data and explored reasons for dissimilar participant responses.MethodsParticipants from open-label antimalarial and antiretroviral interaction trials in two distinct sites (South Africa, n = 18 [all HIV positive]; Tanzania, n = 80 [86% HIV positive]) were asked about ill health and treatment use by sequential use of (1) general enquiries without reference to particular conditions, body systems or treatments, (2) checklists of potential health issues and treatments, (3) in-depth interviews. Participants' experiences of illness and treatment and their reporting behaviour were explored qualitatively, as were trial clinicians' experiences with obtaining participant reports. Outcomes were the number and nature of data by questioning method, themes from qualitative analyses and a theoretical interpretation of participants' experiences.ResultsThere was an overall cumulative increase in the number of reports from general enquiry through checklists to in-depth interview; in South Africa, an additional 12 medical histories, 21 AEs and 27 medications; in Tanzania an additional 260 medical histories, 1 AE and 11 medications. Checklists and interviews facilitated recognition of health issues and treatments, and consideration of what to report. Information was sometimes not reported because participants forgot, it was considered irrelevant or insignificant, or they feared reporting. Some medicine names were not known and answers to questions were considered inferior to blood tests for detecting ill health. South African inpatient volunteers exhibited a "trial citizenship", working to achieve researchers' goals, while Tanzanian outpatients sometimes deferred responsibility for identifying items to report to trial clinicians.ConclusionsQuestioning methods and trial contexts influence the detection of adverse events, medical histories and concomitant medications. There should be further methodological work to investigate these influences and find appropriate questioning methods.

Project description:BackgroundAntipsychotics (APs) have been associated with risk of torsade de Pointes (TdP). This has important public health implications. Therefore, (a) we exploited the public FDA Adverse Event Reporting System (FAERS) to characterize their torsadogenic profile; (b) we collected drug utilization data from 12 European Countries to assess the population exposure over the 2005-2010 period.MethodsFAERS data (2004-2010) were analyzed based on the following criteria: (1) ? 4 cases of TdP/QT abnormalities; (2) Significant Reporting Odds Ratio, ROR [Lower Limit of the 95% confidence interval>1], for TdP/QT abnormalities, adjusted and stratified (Arizona CERT drugs as effect modifiers); (3) ? 4 cases of ventricular arrhythmia/sudden cardiac death (VA/SCD); (4) Significant ROR for VA/SCD; (5) Significant ROR, combined by aggregating TdP/QT abnormalities with VA and SCD. Torsadogenic signals were characterized in terms of signal strength: from Group A (very strong torsadogenic signal: all criteria fulfilled) to group E (unclear/uncertain signal: only 2/5 criteria). Consumption data were retrieved from 12 European Countries and expressed as defined daily doses per 1,000 inhabitants per day (DID).ResultsThirty-five antipsychotics met at least one criterium: 9 agents were classified in Group A (amisulpride, chlorpromazine, clozapine, cyamemazine, haloperidol, olanzapine, quetiapine, risperidone, ziprasidone). In 2010, the overall exposure to antipsychotics varied from 5.94 DID (Estonia) to 13.99 (France, 2009). Considerable increment of Group A agents was found in several Countries (+3.47 in France): the exposure to olanzapine increased across all Countries (+1.84 in France) and peaked 2.96 in Norway; cyamemazine was typically used only in France (2.81 in 2009). Among Group B drugs, levomepromazine peaked 3.78 (Serbia); fluphenazine 1.61 (Slovenia).ConclusionsThis parallel approach through spontaneous reporting and drug utilization analyses highlighted drug- and Country-specific scenarios requiring potential regulatory consideration: levomepromazine (Serbia), fluphenazine (Slovenia), olanzapine (across Europe), cyamemazine (France). This synergy should be encouraged to support future pharmacovigilance activities.

Dataset Information

Detecting drug interactions from adverse-event reports: interaction between paroxetine and pravastatin increases blood glucose levels.

Publications

Detecting drug interactions from adverse-event reports: interaction between paroxetine and pravastatin increases blood glucose levels.

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