Pharmacovigilance Signals of the Opioid Epidemic over 10 Years: Data Mining Methods in the Analysis of Pharmacovigilance Datasets Collecting Adverse Drug Reactions (ADRs) Reported to EudraVigilance (EV) and the FDA Adverse Event Reporting System (FAERS)

Chiappini, Stefania; Vickers-Smith, Rachel; Guirguis, Amira; Corkery, John M.; Martinotti, Giovanni; Harris, Daniel R.; Schifano, Fabrizio

doi:10.3390/ph15060675

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Pharmacovigilance Signals of the Opioid Epidemic over 10 Years: Data Mining Methods in the Analysis of Pharmacovigilance Datasets Collecting Adverse Drug Reactions (ADRs) Reported to EudraVigilance (EV) and the FDA Adverse Event R...

Stefania Chiappini

, Rachel Vickers-Smith

, Amira Guirguis

, John M. Corkery

, Giovanni Martinotti

, Daniel R. Harris, Fabrizio Schifano

Pharmaceuticals, Volume: 15, Issue: 6, Start page: 675

Swansea University Author: Amira Guirguis

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DOI (Published version): 10.3390/ph15060675

Abstract

In the past twenty years, the consumption of opioid medications has reached significant proportions, leading to a rise in drug misuse and abuse and increased opioid dependence and related fatalities. Thus, the purpose of this study was to determine whether there are pharmacovigilance signals of abus...

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Published in:	Pharmaceuticals
ISSN:	1424-8247
Published:	MDPI AG 2022
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URI:	https://cronfa.swan.ac.uk/Record/cronfa60065
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spelling	2022-11-02T12:32:05.6968550 v2 60065 2022-05-24 Pharmacovigilance Signals of the Opioid Epidemic over 10 Years: Data Mining Methods in the Analysis of Pharmacovigilance Datasets Collecting Adverse Drug Reactions (ADRs) Reported to EudraVigilance (EV) and the FDA Adverse Event Reporting System (FAERS) b49270b9a0d580cf4f31f9a1b6c93f87 0000-0001-8255-0660 Amira Guirguis Amira Guirguis true false 2022-05-24 PHAR In the past twenty years, the consumption of opioid medications has reached significant proportions, leading to a rise in drug misuse and abuse and increased opioid dependence and related fatalities. Thus, the purpose of this study was to determine whether there are pharmacovigilance signals of abuse, misuse, and dependence and their nature for the following prescription opioids: codeine, dihydrocodeine, fentanyl, oxycodone, pentazocine, and tramadol. Both the pharmacovigilance datasets EudraVigilance (EV) and the FDA Adverse Events Reporting System (FAERS) were analyzed to identify and describe possible misuse-/abuse-/dependence-related issues. A descriptive analysis of the selected Adverse Drug Reactions (ADRs) was performed, and pharmacovigilance signal measures (i.e., reporting odds ratio, proportional reporting ratio, information component, and empirical Bayesian geometric mean) were computed for preferred terms (PTs) of abuse, misuse, dependence, and withdrawal, as well as PTs eventually related to them (e.g., aggression). From 2003 to 2018, there was an increase in ADR reports for the selected opioids in both datasets. Overall, 16,506 and 130,293 individual ADRs for the selected opioids were submitted to EV and FAERS, respectively. Compared with other opioids, abuse concerns were mostly recorded in relation to fentanyl and oxycodone, while tramadol and oxycodone were more strongly associated with drug dependence and withdrawal. Benzodiazepines, antidepressants, other opioids, antihistamines, recreational drugs (e.g., cocaine and alcohol), and several new psychoactive substances, including mitragynine and cathinones, were the most commonly reported concomitant drugs. ADRs reports in pharmacovigilance databases confirmed the availability of data on the abuse and dependence of prescription opioids and should be considered a resource for monitoring and preventing such issues. Psychiatrists and clinicians prescribing opioids should be aware of their misuse and dependence liability and effects that may accompany their use, especially together with concomitant drugs. Journal Article Pharmaceuticals 15 6 675 MDPI AG 1424-8247 opioids; prescription drug abuse; drug misuse; drug dependence; adverse events; pharmacovigilance; new psychoactive substances 27 5 2022 2022-05-27 10.3390/ph15060675 COLLEGE NANME Pharmacy COLLEGE CODE PHAR Swansea University Not Required This research received no external funding. 2022-11-02T12:32:05.6968550 2022-05-24T08:43:58.6082086 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Stefania Chiappini 0000-0002-6810-1540 1 Rachel Vickers-Smith 0000-0002-7224-8916 2 Amira Guirguis 0000-0001-8255-0660 3 John M. Corkery 0000-0002-3849-817x 4 Giovanni Martinotti 0000-0002-7292-2341 5 Daniel R. Harris 6 Fabrizio Schifano 7 60065__24379__0b7fac793ff54e1490199d8163523639.pdf 60065.pdf 2022-06-23T13:13:11.5601217 Output 565556 application/pdf Version of Record true © 2022 by the authors. This is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license true eng https://creativecommons.org/licenses/by/4.0/
title	Pharmacovigilance Signals of the Opioid Epidemic over 10 Years: Data Mining Methods in the Analysis of Pharmacovigilance Datasets Collecting Adverse Drug Reactions (ADRs) Reported to EudraVigilance (EV) and the FDA Adverse Event Reporting System (FAERS)
spellingShingle	Pharmacovigilance Signals of the Opioid Epidemic over 10 Years: Data Mining Methods in the Analysis of Pharmacovigilance Datasets Collecting Adverse Drug Reactions (ADRs) Reported to EudraVigilance (EV) and the FDA Adverse Event Reporting System (FAERS) Amira Guirguis
title_short	Pharmacovigilance Signals of the Opioid Epidemic over 10 Years: Data Mining Methods in the Analysis of Pharmacovigilance Datasets Collecting Adverse Drug Reactions (ADRs) Reported to EudraVigilance (EV) and the FDA Adverse Event Reporting System (FAERS)
title_full	Pharmacovigilance Signals of the Opioid Epidemic over 10 Years: Data Mining Methods in the Analysis of Pharmacovigilance Datasets Collecting Adverse Drug Reactions (ADRs) Reported to EudraVigilance (EV) and the FDA Adverse Event Reporting System (FAERS)
title_fullStr	Pharmacovigilance Signals of the Opioid Epidemic over 10 Years: Data Mining Methods in the Analysis of Pharmacovigilance Datasets Collecting Adverse Drug Reactions (ADRs) Reported to EudraVigilance (EV) and the FDA Adverse Event Reporting System (FAERS)
title_full_unstemmed	Pharmacovigilance Signals of the Opioid Epidemic over 10 Years: Data Mining Methods in the Analysis of Pharmacovigilance Datasets Collecting Adverse Drug Reactions (ADRs) Reported to EudraVigilance (EV) and the FDA Adverse Event Reporting System (FAERS)
title_sort	Pharmacovigilance Signals of the Opioid Epidemic over 10 Years: Data Mining Methods in the Analysis of Pharmacovigilance Datasets Collecting Adverse Drug Reactions (ADRs) Reported to EudraVigilance (EV) and the FDA Adverse Event Reporting System (FAERS)
author_id_str_mv	b49270b9a0d580cf4f31f9a1b6c93f87
author_id_fullname_str_mv	b49270b9a0d580cf4f31f9a1b6c93f87_***_Amira Guirguis
author	Amira Guirguis
author2	Stefania Chiappini Rachel Vickers-Smith Amira Guirguis John M. Corkery Giovanni Martinotti Daniel R. Harris Fabrizio Schifano
format	Journal article
container_title	Pharmaceuticals
container_volume	15
container_issue	6
container_start_page	675
publishDate	2022
institution	Swansea University
issn	1424-8247
doi_str_mv	10.3390/ph15060675
publisher	MDPI AG
college_str	Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id	facultyofmedicinehealthandlifesciences
hierarchy_top_title	Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id	facultyofmedicinehealthandlifesciences
hierarchy_parent_title	Faculty of Medicine, Health and Life Sciences
department_str	Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
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description	In the past twenty years, the consumption of opioid medications has reached significant proportions, leading to a rise in drug misuse and abuse and increased opioid dependence and related fatalities. Thus, the purpose of this study was to determine whether there are pharmacovigilance signals of abuse, misuse, and dependence and their nature for the following prescription opioids: codeine, dihydrocodeine, fentanyl, oxycodone, pentazocine, and tramadol. Both the pharmacovigilance datasets EudraVigilance (EV) and the FDA Adverse Events Reporting System (FAERS) were analyzed to identify and describe possible misuse-/abuse-/dependence-related issues. A descriptive analysis of the selected Adverse Drug Reactions (ADRs) was performed, and pharmacovigilance signal measures (i.e., reporting odds ratio, proportional reporting ratio, information component, and empirical Bayesian geometric mean) were computed for preferred terms (PTs) of abuse, misuse, dependence, and withdrawal, as well as PTs eventually related to them (e.g., aggression). From 2003 to 2018, there was an increase in ADR reports for the selected opioids in both datasets. Overall, 16,506 and 130,293 individual ADRs for the selected opioids were submitted to EV and FAERS, respectively. Compared with other opioids, abuse concerns were mostly recorded in relation to fentanyl and oxycodone, while tramadol and oxycodone were more strongly associated with drug dependence and withdrawal. Benzodiazepines, antidepressants, other opioids, antihistamines, recreational drugs (e.g., cocaine and alcohol), and several new psychoactive substances, including mitragynine and cathinones, were the most commonly reported concomitant drugs. ADRs reports in pharmacovigilance databases confirmed the availability of data on the abuse and dependence of prescription opioids and should be considered a resource for monitoring and preventing such issues. Psychiatrists and clinicians prescribing opioids should be aware of their misuse and dependence liability and effects that may accompany their use, especially together with concomitant drugs.
published_date	2022-05-27T04:17:51Z
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Pharmacovigilance Signals of the Opioid Epidemic over 10 Years: Data Mining Methods in the Analysis of Pharmacovigilance Datasets Collecting Adverse Drug Reactions (ADRs) Reported to EudraVigilance (EV) and the FDA Adverse Event R...

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