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Statistical Signal Detection as a Routine Pharmacovigilance Practice: Effects of Periodicity and Resignalling Criteria on Quality and Workload

INTRODUCTION: The goal of signal detection in pharmacovigilance (PV) is to detect unknown causal associations between medicines and unexpected events. Statistical methods serve to detect signals and supplement traditional PV methods. Statistical signal detection (SSD) requires decisions about variou...

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Detalles Bibliográficos
Autores principales: Lerch, Magnus, Nowicki, Peter, Manlik, Katrin, Wirsching, Gabriela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4659850/
https://www.ncbi.nlm.nih.gov/pubmed/26391801
http://dx.doi.org/10.1007/s40264-015-0345-1
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author Lerch, Magnus
Nowicki, Peter
Manlik, Katrin
Wirsching, Gabriela
author_facet Lerch, Magnus
Nowicki, Peter
Manlik, Katrin
Wirsching, Gabriela
author_sort Lerch, Magnus
collection PubMed
description INTRODUCTION: The goal of signal detection in pharmacovigilance (PV) is to detect unknown causal associations between medicines and unexpected events. Statistical methods serve to detect signals and supplement traditional PV methods. Statistical signal detection (SSD) requires decisions about various settings that influence the quality and efficiency of SSD, as shown in several studies. To our knowledge, the effects of SSD periodicity and resignalling criteria on the quality and workload of routine SSD have not been published before. OBJECTIVE: To analyse the effects of different periodicities and resignalling criteria on signal detection quality and signal validation workload, and to test the impact of changing the signal threshold for number of cases. METHODS: We calculated signals of disproportionate reporting (SDRs) using thresholds of number of cases (N) ≥3, proportional reporting ratio ≥2 and Chi(2) ≥ 4. We retrospectively simulated recurrent SDR calculation and validation with varying periodicity (quarterly vs. monthly), resignalling criteria, and N ≥ 3 vs. N ≥ 5. RESULTS: Changing the periodicity from quarterly to monthly increased the workload by 46.6 % (0 % signal loss). More restrictive resignalling criteria reduced the workload between 36.3 % (0 % signal loss) and 74.1 % (50 % signal loss). For N ≥ 3, the most efficient monthly SSD resignalling criterion reduced the workload by 36.3 % and detected all true signals earlier than quarterly SSD. N ≥ 5 reduced the workload between 13.8 and 21.4 % (0 % signal loss). CONCLUSIONS: In real-life PV practice, signal detection and validation are recurrent periodic activities. Some true signals are only discovered upon resignalling. Our results demonstrate resignalling criteria with high signal detection quality and high efficiency. We found potential earlier detection of true signals using monthly SSD. Additional studies about resignalling should be performed to complement our findings.
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spelling pubmed-46598502015-12-03 Statistical Signal Detection as a Routine Pharmacovigilance Practice: Effects of Periodicity and Resignalling Criteria on Quality and Workload Lerch, Magnus Nowicki, Peter Manlik, Katrin Wirsching, Gabriela Drug Saf Original Research Article INTRODUCTION: The goal of signal detection in pharmacovigilance (PV) is to detect unknown causal associations between medicines and unexpected events. Statistical methods serve to detect signals and supplement traditional PV methods. Statistical signal detection (SSD) requires decisions about various settings that influence the quality and efficiency of SSD, as shown in several studies. To our knowledge, the effects of SSD periodicity and resignalling criteria on the quality and workload of routine SSD have not been published before. OBJECTIVE: To analyse the effects of different periodicities and resignalling criteria on signal detection quality and signal validation workload, and to test the impact of changing the signal threshold for number of cases. METHODS: We calculated signals of disproportionate reporting (SDRs) using thresholds of number of cases (N) ≥3, proportional reporting ratio ≥2 and Chi(2) ≥ 4. We retrospectively simulated recurrent SDR calculation and validation with varying periodicity (quarterly vs. monthly), resignalling criteria, and N ≥ 3 vs. N ≥ 5. RESULTS: Changing the periodicity from quarterly to monthly increased the workload by 46.6 % (0 % signal loss). More restrictive resignalling criteria reduced the workload between 36.3 % (0 % signal loss) and 74.1 % (50 % signal loss). For N ≥ 3, the most efficient monthly SSD resignalling criterion reduced the workload by 36.3 % and detected all true signals earlier than quarterly SSD. N ≥ 5 reduced the workload between 13.8 and 21.4 % (0 % signal loss). CONCLUSIONS: In real-life PV practice, signal detection and validation are recurrent periodic activities. Some true signals are only discovered upon resignalling. Our results demonstrate resignalling criteria with high signal detection quality and high efficiency. We found potential earlier detection of true signals using monthly SSD. Additional studies about resignalling should be performed to complement our findings. Springer International Publishing 2015-09-21 2015 /pmc/articles/PMC4659850/ /pubmed/26391801 http://dx.doi.org/10.1007/s40264-015-0345-1 Text en © The Author(s) 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Research Article
Lerch, Magnus
Nowicki, Peter
Manlik, Katrin
Wirsching, Gabriela
Statistical Signal Detection as a Routine Pharmacovigilance Practice: Effects of Periodicity and Resignalling Criteria on Quality and Workload
title Statistical Signal Detection as a Routine Pharmacovigilance Practice: Effects of Periodicity and Resignalling Criteria on Quality and Workload
title_full Statistical Signal Detection as a Routine Pharmacovigilance Practice: Effects of Periodicity and Resignalling Criteria on Quality and Workload
title_fullStr Statistical Signal Detection as a Routine Pharmacovigilance Practice: Effects of Periodicity and Resignalling Criteria on Quality and Workload
title_full_unstemmed Statistical Signal Detection as a Routine Pharmacovigilance Practice: Effects of Periodicity and Resignalling Criteria on Quality and Workload
title_short Statistical Signal Detection as a Routine Pharmacovigilance Practice: Effects of Periodicity and Resignalling Criteria on Quality and Workload
title_sort statistical signal detection as a routine pharmacovigilance practice: effects of periodicity and resignalling criteria on quality and workload
topic Original Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4659850/
https://www.ncbi.nlm.nih.gov/pubmed/26391801
http://dx.doi.org/10.1007/s40264-015-0345-1
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