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Hecker M, Frahm N, Bachmann P, Debus JL, Haker MC, Mashhadiakbar P, Langhorst SE, Baldt J, Streckenbach B, Heidler F, Zettl UK. Screening for severe drug-drug interactions in patients with multiple sclerosis: A comparison of three drug interaction databases. Front Pharmacol 2022; 13:946351. [PMID: 36034780 PMCID: PMC9416235 DOI: 10.3389/fphar.2022.946351] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 07/04/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Patients with multiple sclerosis (MS) often undergo complex treatment regimens, resulting in an increased risk of polypharmacy and potential drug-drug interactions (pDDIs). Drug interaction databases are useful for identifying pDDIs to support safer medication use. Objective: To compare three different screening tools regarding the detection and classification of pDDIs in a cohort of MS patients. Furthermore, we aimed at ascertaining sociodemographic and clinical factors that are associated with the occurrence of severe pDDIs. Methods: The databases Stockley's, Drugs.com and MediQ were used to identify pDDIs by screening the medication schedules of 627 patients. We determined the overlap of the identified pDDIs and the level of agreement in pDDI severity ratings between the three databases. Logistic regression analyses were conducted to determine patient risk factors of having a severe pDDI. Results: The most different pDDIs were identified using MediQ (n = 1,161), followed by Drugs.com (n = 923) and Stockley's (n = 706). The proportion of pDDIs classified as severe was much higher for Stockley's (37.4%) than for Drugs.com (14.4%) and MediQ (0.9%). Overall, 1,684 different pDDIs were identified by at least one database, of which 318 pDDIs (18.9%) were detected with all three databases. Only 55 pDDIs (3.3%) have been reported with the same severity level across all databases. A total of 336 pDDIs were classified as severe (271 pDDIs by one database, 59 by two databases and 6 by three databases). Stockley's and Drugs.com revealed 47 and 23 severe pDDIs, respectively, that were not included in the other databases. At least one severe pDDI was found for 35.2% of the patients. The most common severe pDDI was the combination of acetylsalicylic acid with enoxaparin, and citalopram was the drug most frequently involved in different severe pDDIs. The strongest predictors of having a severe pDDI were a greater number of drugs taken, an older age, living alone, a higher number of comorbidities and a lower educational level. Conclusions: The information on pDDIs are heterogeneous between the databases examined. More than one resource should be used in clinical practice to evaluate pDDIs. Regular medication reviews and exchange of information between treating physicians can help avoid severe pDDIs.
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Affiliation(s)
- Michael Hecker
- Division of Neuroimmunology, Department of Neurology, Rostock University Medical Center, Rostock, Germany
| | - Niklas Frahm
- Division of Neuroimmunology, Department of Neurology, Rostock University Medical Center, Rostock, Germany
| | - Paula Bachmann
- Division of Neuroimmunology, Department of Neurology, Rostock University Medical Center, Rostock, Germany
| | - Jane Louisa Debus
- Division of Neuroimmunology, Department of Neurology, Rostock University Medical Center, Rostock, Germany
| | - Marie-Celine Haker
- Division of Neuroimmunology, Department of Neurology, Rostock University Medical Center, Rostock, Germany
| | - Pegah Mashhadiakbar
- Division of Neuroimmunology, Department of Neurology, Rostock University Medical Center, Rostock, Germany
| | - Silvan Elias Langhorst
- Division of Neuroimmunology, Department of Neurology, Rostock University Medical Center, Rostock, Germany
| | - Julia Baldt
- Division of Neuroimmunology, Department of Neurology, Rostock University Medical Center, Rostock, Germany.,Ecumenic Hainich Hospital gGmbH, Mühlhausen, Germany
| | - Barbara Streckenbach
- Division of Neuroimmunology, Department of Neurology, Rostock University Medical Center, Rostock, Germany.,Ecumenic Hainich Hospital gGmbH, Mühlhausen, Germany
| | | | - Uwe Klaus Zettl
- Division of Neuroimmunology, Department of Neurology, Rostock University Medical Center, Rostock, Germany
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Rosa GM, Baccino D, Valbusa A, Scala C, Barra F, Brunelli C, Ferrero S. Cardiovascular effects of antimuscarinic agents and beta3-adrenergic receptor agonist for the treatment of overactive bladder. Expert Opin Drug Saf 2018. [PMID: 29542337 DOI: 10.1080/14740338.2018.1453496] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
INTRODUCTION Overactive bladder (OAB) syndrome is common in the general population, particularly in elderly patients. Antimuscarinic drugs (AMs) are considered the mainstay pharmaceutical treatment of OAB whereas β3-adrenoceptor agonists, such as mirabegron, represent a good alternative. Owing to the important role of muscarinic and β3 receptors in cardiovascular (CV) tissue and to the fact that OAB patients often have CV comorbidities, the safety-profile of these drugs constitute an important challenge. AREAS COVERED The aim of this review is to evaluate the CV effects of AMs and mirabegron in OAB. A systematic literature search from inception until December 2017 was performed on PubMed and Medline. EXPERT OPINION AMs are generally considered to have good CV safety profile but, however, they may cause undesirable adverse events, such as dry mouth, constipation. CV AEs are rare but noteworthy, the most common CV consequences related to the use of these drugs are constituted by an increase in HR and QT interval. Mirabegron has similar efficacy and tolerability to AMs but causes less adverse events, with either modest hypertension and modest increase in HR (<5 bpm) being the most commonly reported.
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Affiliation(s)
- Gian Marco Rosa
- a Department of Internal Medicine, Cardiology , Ospedale Policlinico San Martino , Genoa , Italy
| | - Danilo Baccino
- a Department of Internal Medicine, Cardiology , Ospedale Policlinico San Martino , Genoa , Italy
| | - Alberto Valbusa
- a Department of Internal Medicine, Cardiology , Ospedale Policlinico San Martino , Genoa , Italy
| | - Carolina Scala
- b Academic Unit of Obstetrics and Gynecology , Ospedale Policlinico San Martino , Genoa , Italy.,c Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DiNOGMI) , University of Genoa , Genoa , Italy
| | - Fabio Barra
- b Academic Unit of Obstetrics and Gynecology , Ospedale Policlinico San Martino , Genoa , Italy.,c Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DiNOGMI) , University of Genoa , Genoa , Italy
| | - Claudio Brunelli
- a Department of Internal Medicine, Cardiology , Ospedale Policlinico San Martino , Genoa , Italy
| | - Simone Ferrero
- b Academic Unit of Obstetrics and Gynecology , Ospedale Policlinico San Martino , Genoa , Italy.,c Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DiNOGMI) , University of Genoa , Genoa , Italy
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