Detecting Drug Interactions From Adverse-Event Reports: Interaction Between Paroxetine and Pravastatin Increases Blood Glucose Levels

Tatonetti, Nicholas P.; Denny, Joshua C.; Murphy, S M; Fernald, GH; Krishnan, Gomathi; Castro, Vı́ctor; Yue, Patrick; Tsau, PS; Kohane, Isaac S.; Roden, DM; Altman, Russ B.

doi:10.1038/clpt.2011.83

Cited by 177 publications

(151 citation statements)

References 32 publications

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“…The main finding of this study was that although paroxetine itself produced a trend toward impaired glycemic control and insulin secretion in diabetic rats, comedication with paroxetine and pravastatin further deteriorated glucose homeostasis, which was in accordance with clinical reports [14][15][16] . Compared with the DM rats, the DM-CO rats displayed lower insulin levels in both the serum and pancreas, which was in line with a decrease in the expression of pancreatic Insulin-2 mRNA, inferring that insulin biosynthesis was inhibited.…”

Section: Discussionsupporting

confidence: 78%

“…However, multiple reports have demonstrated that comedication with pravastatin and paroxetine can increase the risk of elevated blood glucose levels in diabetic patients [14][15][16] , although neither pravastatin nor paroxetine alone have shown an effect on glucose levels. The real mechanism leading to the adverse drug reaction Paroxetine is metabolized in the liver mainly by CYP2D6 [17] .…”

Section: Introductionmentioning

confidence: 99%

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Co-administration of paroxetine and pravastatin causes deregulation of glucose homeostasis in diabetic rats via enhanced paroxetine exposure

Zhang

et al. 2014

Acta Pharmacol Sin

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Aim: Clinical evidence shows that co-administration of pravastatin and paroxetine deregulates glucose homeostasis in diabetic patients. The aim of this study was to verify this phenomenon in diabetic rats and to elucidate the underlying mechanisms. Methods: Diabetes mellitus was induced in male SD rats by a high-fat diet combined with a low-dose streptozotocin injection. The rats were orally administered paroxetine (10 mg/kg) and pravastatin (10 mg/d) or both the drugs daily for 28 d. The pharmacokinetics of paroxetine and pravastatin were examined on d 1 and d 28. Biochemical parameters including serum insulin, glucose and lipids were monitored during the treatments. An insulin-secreting cell line (INS-1) was used for measuring insulin secretion. Results: In diabetic rats, co-administration of paroxetine and pravastatin markedly increased the concentrations of both the drugs compared with administration of each drug alone. Furthermore, co-administration severely impaired glucose homeostasis in diabetic rats, as demonstrated by significantly increased serum glucose level, decreased serum and pancreatic insulin levels, and decreased pancreatic Insulin-2 mRNA and tryptophan hydroxylase-1 (Tph-1) mRNA levels. Treatment of INS-1 cells with paroxetine (5 and 10 μmol/L) significantly inhibited insulin secretion, decreased the intracellular insulin, 5-HT, Insulin-2 mRNA and Tph-1 mRNA levels. Treatment of the cells with pravastatin (10 μmol/L) significantly stimulated insulin secretion, which was weakened by co-treatment with paroxetine. Conclusion: Paroxetine inhibits insulin secretion at least via decreasing intracellular 5-HT and insulin biosynthesis. The deregulation of glucose homeostasis by co-administration of paroxetine and pravastatin in diabetic rats can be attributed to enhanced paroxetine exposure.

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Section: Discussionsupporting

confidence: 78%

Section: Introductionmentioning

confidence: 99%

Co-administration of paroxetine and pravastatin causes deregulation of glucose homeostasis in diabetic rats via enhanced paroxetine exposure

Zhang

et al. 2014

Acta Pharmacol Sin

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“…DDIs are usually discovered during nonmarketing surveillance 7, 8. It is already known that the concomitant use of statins and specific nonstatin drugs increases the risk of rhabdomyolysis.…”

Section: Introductionmentioning

confidence: 99%

Onset timing of statin‐induced musculoskeletal adverse events and concomitant drug‐associated shift in onset timing of MAEs

Akimoto

Negishi

Oshima

et al. 2018

Pharmacology Res & Perspec

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To evaluate the onset timing of musculoskeletal adverse events (MAEs) that develop during statin monotherapy and to determine whether concomitant drugs used concurrently with statin therapy shifts the onset timing of MAEs. Cases in which statins (atorvastatin, rosuvastatin, simvastatin, lovastatin, fluvastatin, pitavastatin, and pravastatin) were prescribed were extracted from the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) Data Files. The onset timing of MAEs during statin monotherapy was evaluated by determining the difference between statin start date and MAE onset date. The use of concomitant drugs with statin therapy was included in the analysis. Statins used in combination with concomitant drugs were compared with statin monotherapy to determine if the use of concomitant drugs shifted the onset timing of MAEs. The onset of MAEs was significantly faster with atorvastatin and rosuvastatin than with simvastatin. A difference in onset timing was not detected with other statins because the number of cases was too small for analysis. When evaluating concomitant drug use, the concomitant drugs that shifted the onset timing of MAEs could not be detected. Statins with strong low‐density lipoprotein cholesterol‐lowering effects (atorvastatin and rosuvastatin) contributed not only to a high risk of MAE onset, but also to a shorter time‐to‐onset. No concomitant drug significantly shifted the onset timing of MAEs when used concurrently with statins.

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“…Data mining methods in pharmacovigilance have been used with several goals, [8,9] (i) in order to automate the search of publications concerning ADR in Medline, [11] (ii) to correlate and predict post-marketing adverse drug effects based on screening data from public databases of chemical structures like Pubchem, [12] (iii) to develop new algorithms to detect new or latent multi-drug adverse events in Adverse Event Reporting System database [5] and (iv) to find out new pharmacovigilance signal by mining EHR data. [13,14] For example, in a recently published work, [13] Tatonetti NP et al…”

Section: Introductionmentioning

confidence: 99%

Detection of Drug–Drug Interactions Inducing Acute Kidney Injury by Electronic Health Records Mining

et al. 2015

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Objective: While risk of Acute Kidney Injury (AKI) is well-documented as adverse effects of some drugs, few studies have assessed relationship between Drug-Drug Interactions (DDI) and AKI. Our objective was to develop an algorithm capable of detecting potential signals on this relationship by mining retrospectively data from an electronic health record. 3 Key Points-The re-use of data from Electronic Health Record (EHR) generated by real clinical activities for pharmacoepidemiological studies is booming, it seemed that DDIs could be identified by mining such databases.-We have developed a new signal detection algorithm using data mining techniques and the RIFLE criteria capable to re-use real care data from EHR in order to identify potential pharmacovigilance signal concerning DDIs and AKI.-This study confirms that real care data from EHRs could be utilized to identify new pharmacovigilance signal concerning DDIs.

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Detecting Drug Interactions From Adverse-Event Reports: Interaction Between Paroxetine and Pravastatin Increases Blood Glucose Levels

Cited by 177 publications

References 32 publications

Co-administration of paroxetine and pravastatin causes deregulation of glucose homeostasis in diabetic rats via enhanced paroxetine exposure

Co-administration of paroxetine and pravastatin causes deregulation of glucose homeostasis in diabetic rats via enhanced paroxetine exposure

Onset timing of statin‐induced musculoskeletal adverse events and concomitant drug‐associated shift in onset timing of MAEs

Detection of Drug–Drug Interactions Inducing Acute Kidney Injury by Electronic Health Records Mining

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