Cargando…

Investigating Overlap in Signals from EVDAS, FAERS, and VigiBase(®)

INTRODUCTION: The Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) and VigiBase(®) are two established databases for safety monitoring of medicinal products, recently complemented with the EudraVigilance Data Analysis System (EVDAS). OBJECTIVE: Signals of disproportionate re...

Descripción completa

Detalles Bibliográficos
Autores principales: Vogel, Ulrich, van Stekelenborg, John, Dreyfus, Brian, Garg, Anju, Habib, Marian, Hosain, Romana, Wisniewski, Antoni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7105447/
https://www.ncbi.nlm.nih.gov/pubmed/32020559
http://dx.doi.org/10.1007/s40264-019-00899-y
_version_ 1783512403500072960
author Vogel, Ulrich
van Stekelenborg, John
Dreyfus, Brian
Garg, Anju
Habib, Marian
Hosain, Romana
Wisniewski, Antoni
author_facet Vogel, Ulrich
van Stekelenborg, John
Dreyfus, Brian
Garg, Anju
Habib, Marian
Hosain, Romana
Wisniewski, Antoni
author_sort Vogel, Ulrich
collection PubMed
description INTRODUCTION: The Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) and VigiBase(®) are two established databases for safety monitoring of medicinal products, recently complemented with the EudraVigilance Data Analysis System (EVDAS). OBJECTIVE: Signals of disproportionate reporting (SDRs) can characterize the reporting profile of a drug, accounting for the distribution of all drugs and all events in the database. This study aims to quantify the redundancy among the three databases when characterized by two disproportionality-based analyses (DPA). METHODS: SDRs for 100 selected products were identified with two sets of thresholds (standard EudraVigilance SDR criteria for all vs Bayesian approach for FAERS and VigiBase(®)). Per product and database, the presence or absence of SDRs was determined and compared. Adverse events were considered at three levels: MedDRA(®) Preferred Term (PT), High Level Term (HLT), and HLT combined with Standardized MedDRA(®) Query (SMQ). Redundancy was measured in terms of recall (SDRs in EVDAS divided by SDRs from any database) and overlap (SDRs in EVDAS and at least one other database, divided by SDRs in EVDAS). Covariates with potential impact on results were explored with linear regression models. RESULTS: The median overlap between EVDAS and FAERS or VigiBase(®) was 85.0% at the PT level, 94.5% at the HLT level, and 97.7% at the HLT or SMQ level. The corresponding median recall of signals in EVDAS as a percentage of all signals generated in all three databases was 59.4%, 74.1%, and 87.9% at the PT, HLT, and HLT or SMQ levels, respectively. The overlap difference is partially explained by the relative number of EU cases in EudraVigilance and the ratio of EVDAS cases and FAERS cases, presumably due to differences in marketing authorizations, or market penetration in different regions. Products with few cases in EVDAS (< 1500) also display limited recall of signals relative to FAERs/VigiBase(®). Time-on-market does not predict signal redundancy between the three databases. The choice of the DPA has an expected but somewhat small effect on redundancy. CONCLUSIONS: Organizations typically consider regulatory expectations, operating performance (e.g., positive predictive value), and procedural complexity when selecting databases for signal management. As SDRs can be seen as a proxy of general reporting characteristics identifiable in a systematic screening process, our results indicate that, for most products, these characteristics are largely similar in each of the databases. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s40264-019-00899-y) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-7105447
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Springer International Publishing
record_format MEDLINE/PubMed
spelling pubmed-71054472020-04-03 Investigating Overlap in Signals from EVDAS, FAERS, and VigiBase(®) Vogel, Ulrich van Stekelenborg, John Dreyfus, Brian Garg, Anju Habib, Marian Hosain, Romana Wisniewski, Antoni Drug Saf Original Research Article INTRODUCTION: The Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) and VigiBase(®) are two established databases for safety monitoring of medicinal products, recently complemented with the EudraVigilance Data Analysis System (EVDAS). OBJECTIVE: Signals of disproportionate reporting (SDRs) can characterize the reporting profile of a drug, accounting for the distribution of all drugs and all events in the database. This study aims to quantify the redundancy among the three databases when characterized by two disproportionality-based analyses (DPA). METHODS: SDRs for 100 selected products were identified with two sets of thresholds (standard EudraVigilance SDR criteria for all vs Bayesian approach for FAERS and VigiBase(®)). Per product and database, the presence or absence of SDRs was determined and compared. Adverse events were considered at three levels: MedDRA(®) Preferred Term (PT), High Level Term (HLT), and HLT combined with Standardized MedDRA(®) Query (SMQ). Redundancy was measured in terms of recall (SDRs in EVDAS divided by SDRs from any database) and overlap (SDRs in EVDAS and at least one other database, divided by SDRs in EVDAS). Covariates with potential impact on results were explored with linear regression models. RESULTS: The median overlap between EVDAS and FAERS or VigiBase(®) was 85.0% at the PT level, 94.5% at the HLT level, and 97.7% at the HLT or SMQ level. The corresponding median recall of signals in EVDAS as a percentage of all signals generated in all three databases was 59.4%, 74.1%, and 87.9% at the PT, HLT, and HLT or SMQ levels, respectively. The overlap difference is partially explained by the relative number of EU cases in EudraVigilance and the ratio of EVDAS cases and FAERS cases, presumably due to differences in marketing authorizations, or market penetration in different regions. Products with few cases in EVDAS (< 1500) also display limited recall of signals relative to FAERs/VigiBase(®). Time-on-market does not predict signal redundancy between the three databases. The choice of the DPA has an expected but somewhat small effect on redundancy. CONCLUSIONS: Organizations typically consider regulatory expectations, operating performance (e.g., positive predictive value), and procedural complexity when selecting databases for signal management. As SDRs can be seen as a proxy of general reporting characteristics identifiable in a systematic screening process, our results indicate that, for most products, these characteristics are largely similar in each of the databases. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s40264-019-00899-y) contains supplementary material, which is available to authorized users. Springer International Publishing 2020-02-04 2020 /pmc/articles/PMC7105447/ /pubmed/32020559 http://dx.doi.org/10.1007/s40264-019-00899-y Text en © TransCelerate BioPharma Inc. under exclusive licence to Springer Nature Switzerland AG 2020 Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Original Research Article
Vogel, Ulrich
van Stekelenborg, John
Dreyfus, Brian
Garg, Anju
Habib, Marian
Hosain, Romana
Wisniewski, Antoni
Investigating Overlap in Signals from EVDAS, FAERS, and VigiBase(®)
title Investigating Overlap in Signals from EVDAS, FAERS, and VigiBase(®)
title_full Investigating Overlap in Signals from EVDAS, FAERS, and VigiBase(®)
title_fullStr Investigating Overlap in Signals from EVDAS, FAERS, and VigiBase(®)
title_full_unstemmed Investigating Overlap in Signals from EVDAS, FAERS, and VigiBase(®)
title_short Investigating Overlap in Signals from EVDAS, FAERS, and VigiBase(®)
title_sort investigating overlap in signals from evdas, faers, and vigibase(®)
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7105447/
https://www.ncbi.nlm.nih.gov/pubmed/32020559
http://dx.doi.org/10.1007/s40264-019-00899-y
work_keys_str_mv AT vogelulrich investigatingoverlapinsignalsfromevdasfaersandvigibase
AT vanstekelenborgjohn investigatingoverlapinsignalsfromevdasfaersandvigibase
AT dreyfusbrian investigatingoverlapinsignalsfromevdasfaersandvigibase
AT garganju investigatingoverlapinsignalsfromevdasfaersandvigibase
AT habibmarian investigatingoverlapinsignalsfromevdasfaersandvigibase
AT hosainromana investigatingoverlapinsignalsfromevdasfaersandvigibase
AT wisniewskiantoni investigatingoverlapinsignalsfromevdasfaersandvigibase