Dataset Information

Network Analysis for Signal Detection in Spontaneous Adverse Event Reporting Database: Application of Network Weighting Normalization to Characterize Cardiovascular Drug Safety.

ABSTRACT:

Introduction

Signal detection yields confirmed signals in only 2.1%, which imposes a heavy burden on the pharmacovigilance system in the European Union.

Objectives

We aimed to develop a network theoretical metric to increase the confirmed signal ratio of individual case safety report (ICSR) networks.

Methods

ICSRs of five cardiovascular adverse events were requested from EudraVigilance. We developed Vigilace™, a web-based application to build network representation of ICSRs. Three network-based signal scores, which we termed NEWS (normalized edge weight for signals) scores, were calculated by normalizing the weight of each edge in the report-based weighted network by the weight of the same edge in topological weighted networks. Depending on the third node in topological network edges, we defined full-, adverse event-, and drug-type NEWS scores. Area under the receiver operating characteristic curves (AUROC) were analyzed to compare the reporting odds ratio (ROR) and NEWS scores.

Results

Overall, 72,475 ICSRs were accessed from EudraVigilance. Drug-type NEWS (NEWS_D) score performed better (DeLong test, p-value <0.05) compared with the ROR in case of four adverse events: acute myocardial infarction (AUROC: 0.856 vs. 0.720), arrhythmia (0.657 vs. 0.614), pulmonary hypertension (0.861 vs. 0.720), and QT prolongation (0.830 vs. 0.749). Postural orthostatic tachycardia syndrome was excluded due to the lack of reference data.

Conclusion

This is the first demonstration that report-based weighting normalized by topological weighting of co-reported drugs, which we termed as NEWS_D score, can perform better compared with the ROR. An application was developed for ICSR network analysis that facilitates the calculation of this score.

SUBMITTER: Petervari M

PROVIDER: S-EPMC9561003 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Network Analysis for Signal Detection in Spontaneous Adverse Event Reporting Database: Application of Network Weighting Normalization to Characterize Cardiovascular Drug Safety.

Pétervári Mátyás M Benczik Bettina B Balogh Olivér M OM Petrovich Balázs B Ágg Bence B Ferdinandy Péter P

Drug safety 20221006 11

<h4>Introduction</h4>Signal detection yields confirmed signals in only 2.1%, which imposes a heavy burden on the pharmacovigilance system in the European Union.<h4>Objectives</h4>We aimed to develop a network theoretical metric to increase the confirmed signal ratio of individual case safety report (ICSR) networks.<h4>Methods</h4>ICSRs of five cardiovascular adverse events were requested from EudraVigilance. We developed Vigilace™, a web-based application to build network representation of ICSRs ...[more]

PMID: 36198930

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Dataset Information

Network Analysis for Signal Detection in Spontaneous Adverse Event Reporting Database: Application of Network Weighting Normalization to Characterize Cardiovascular Drug Safety.

Introduction

Objectives

Methods

Results

Conclusion

Publications

Network Analysis for Signal Detection in Spontaneous Adverse Event Reporting Database: Application of Network Weighting Normalization to Characterize Cardiovascular Drug Safety.

Similar Datasets

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