Cargando…
Change Point Analysis for Detecting Vaccine Safety Signals
It is important to detect signals of abrupt changes in adverse event reporting in order to notice public safety concerns and take prompt action, especially for vaccines under national immunization programs. In this study, we assessed the applicability of change point analysis (CPA) for signal detect...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8001699/ https://www.ncbi.nlm.nih.gov/pubmed/33801188 http://dx.doi.org/10.3390/vaccines9030206 |
_version_ | 1783671291610398720 |
---|---|
author | You, Seung-Hun Jang, Eun Jin Kim, Myo-Song Lee, Min-Taek Kang, Ye-Jin Lee, Jae-Eun Eom, Joo-Hyeon Jung, Sun-Young |
author_facet | You, Seung-Hun Jang, Eun Jin Kim, Myo-Song Lee, Min-Taek Kang, Ye-Jin Lee, Jae-Eun Eom, Joo-Hyeon Jung, Sun-Young |
author_sort | You, Seung-Hun |
collection | PubMed |
description | It is important to detect signals of abrupt changes in adverse event reporting in order to notice public safety concerns and take prompt action, especially for vaccines under national immunization programs. In this study, we assessed the applicability of change point analysis (CPA) for signal detection in vaccine safety surveillance. The performances of three CPA methods, namely Bayesian change point analysis, Taylor’s change point analysis (Taylor-CPA), and environmental time series change point detection (EnvCpt), were assessed via simulated data with assumptions for the baseline number of events and degrees of change. The analysis was validated using the Korea Adverse Event Reporting System (KAERS) database. In the simulation study, the Taylor-CPA method exhibited better results for the detection of a change point (accuracy of 96% to 100%, sensitivity of 7% to 100%, specificity of 98% to 100%, positive predictive value of 25% to 85%, negative predictive value of 96% to 100%, and balanced accuracy of 53% to 100%) than the other two CPA methods. When the CPA methods were applied to reports of syncope or dizziness following human papillomavirus (HPV) immunization in the KAERS database, Taylor-CPA and EnvCpt detected a change point (Q2/2013), which was consistent with actual public safety concerns. CPA can be applied as an efficient tool for the early detection of vaccine safety signals. |
format | Online Article Text |
id | pubmed-8001699 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-80016992021-03-28 Change Point Analysis for Detecting Vaccine Safety Signals You, Seung-Hun Jang, Eun Jin Kim, Myo-Song Lee, Min-Taek Kang, Ye-Jin Lee, Jae-Eun Eom, Joo-Hyeon Jung, Sun-Young Vaccines (Basel) Article It is important to detect signals of abrupt changes in adverse event reporting in order to notice public safety concerns and take prompt action, especially for vaccines under national immunization programs. In this study, we assessed the applicability of change point analysis (CPA) for signal detection in vaccine safety surveillance. The performances of three CPA methods, namely Bayesian change point analysis, Taylor’s change point analysis (Taylor-CPA), and environmental time series change point detection (EnvCpt), were assessed via simulated data with assumptions for the baseline number of events and degrees of change. The analysis was validated using the Korea Adverse Event Reporting System (KAERS) database. In the simulation study, the Taylor-CPA method exhibited better results for the detection of a change point (accuracy of 96% to 100%, sensitivity of 7% to 100%, specificity of 98% to 100%, positive predictive value of 25% to 85%, negative predictive value of 96% to 100%, and balanced accuracy of 53% to 100%) than the other two CPA methods. When the CPA methods were applied to reports of syncope or dizziness following human papillomavirus (HPV) immunization in the KAERS database, Taylor-CPA and EnvCpt detected a change point (Q2/2013), which was consistent with actual public safety concerns. CPA can be applied as an efficient tool for the early detection of vaccine safety signals. MDPI 2021-03-02 /pmc/articles/PMC8001699/ /pubmed/33801188 http://dx.doi.org/10.3390/vaccines9030206 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ). |
spellingShingle | Article You, Seung-Hun Jang, Eun Jin Kim, Myo-Song Lee, Min-Taek Kang, Ye-Jin Lee, Jae-Eun Eom, Joo-Hyeon Jung, Sun-Young Change Point Analysis for Detecting Vaccine Safety Signals |
title | Change Point Analysis for Detecting Vaccine Safety Signals |
title_full | Change Point Analysis for Detecting Vaccine Safety Signals |
title_fullStr | Change Point Analysis for Detecting Vaccine Safety Signals |
title_full_unstemmed | Change Point Analysis for Detecting Vaccine Safety Signals |
title_short | Change Point Analysis for Detecting Vaccine Safety Signals |
title_sort | change point analysis for detecting vaccine safety signals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8001699/ https://www.ncbi.nlm.nih.gov/pubmed/33801188 http://dx.doi.org/10.3390/vaccines9030206 |
work_keys_str_mv | AT youseunghun changepointanalysisfordetectingvaccinesafetysignals AT jangeunjin changepointanalysisfordetectingvaccinesafetysignals AT kimmyosong changepointanalysisfordetectingvaccinesafetysignals AT leemintaek changepointanalysisfordetectingvaccinesafetysignals AT kangyejin changepointanalysisfordetectingvaccinesafetysignals AT leejaeeun changepointanalysisfordetectingvaccinesafetysignals AT eomjoohyeon changepointanalysisfordetectingvaccinesafetysignals AT jungsunyoung changepointanalysisfordetectingvaccinesafetysignals |