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Reducing the noise in signal detection of adverse drug reactions by standardizing the background: a pilot study on analyses of proportional reporting ratios-by-therapeutic area
PURPOSE: Disproportionality screening analysis is acknowledged as a tool for performing signal detection in databases of adverse drug reactions (ADRs), e.g., in the European Union (EU) Drug Authority setting. The purpose of this study was to explore the possibility of decreasing false-positive signa...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3978377/ https://www.ncbi.nlm.nih.gov/pubmed/24599513 http://dx.doi.org/10.1007/s00228-014-1658-1 |
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author | Grundmark, Birgitta Holmberg, Lars Garmo, Hans Zethelius, Björn |
author_facet | Grundmark, Birgitta Holmberg, Lars Garmo, Hans Zethelius, Björn |
author_sort | Grundmark, Birgitta |
collection | PubMed |
description | PURPOSE: Disproportionality screening analysis is acknowledged as a tool for performing signal detection in databases of adverse drug reactions (ADRs), e.g., in the European Union (EU) Drug Authority setting. The purpose of this study was to explore the possibility of decreasing false-positive signals of disproportionate reporting (SDR) by calculating the proportional reporting ratio (PRR)-by-therapeutic area (TA), while still maintaining the ability to detect relevant SDRs. METHODS: In the EudraVigilance (EV) Database, output from PRR calculated with a restricted TA comparator background was compared in detail to output from conventional authority-setting PRR calculations for four drugs: bicalutamide, abiraterone, metformin, and vildagliptin, within the TAs of prostate gland disease and type 2 diabetes mellitus. RESULTS: ADR reports per investigated drug ranged from 2,400 to 50,000. The PRR-TA’s ability to detect true-positive SDRs (as acknowledged in approved labeling) was increased compared to the conventional PRR, and performed 8–31 % better than a recently proposed stricter EU-SDR definition. The PRR-TA removed false SDRs confounded by disease or disease spill-over by up to 63 %, while retaining/increasing the number of unclassified SDRs relevant for manual validation, and thereby improving the ratio between confounded SDRs (i.e., noise) and unclassified SDRs for all investigated drugs (possible signals). CONCLUSIONS: The performance of the PRR was improved by background restriction with the PRR-TA method; the number of false-positive SDRs decreased, and the ability to detect true-positive SDRs increased, improving the signal-to-noise ratio. Further development and validation of the method is needed within other TAs and databases, and for disproportionality analysis methods. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00228-014-1658-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-3978377 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-39783772014-04-22 Reducing the noise in signal detection of adverse drug reactions by standardizing the background: a pilot study on analyses of proportional reporting ratios-by-therapeutic area Grundmark, Birgitta Holmberg, Lars Garmo, Hans Zethelius, Björn Eur J Clin Pharmacol Pharmacoepidemiology and Prescription PURPOSE: Disproportionality screening analysis is acknowledged as a tool for performing signal detection in databases of adverse drug reactions (ADRs), e.g., in the European Union (EU) Drug Authority setting. The purpose of this study was to explore the possibility of decreasing false-positive signals of disproportionate reporting (SDR) by calculating the proportional reporting ratio (PRR)-by-therapeutic area (TA), while still maintaining the ability to detect relevant SDRs. METHODS: In the EudraVigilance (EV) Database, output from PRR calculated with a restricted TA comparator background was compared in detail to output from conventional authority-setting PRR calculations for four drugs: bicalutamide, abiraterone, metformin, and vildagliptin, within the TAs of prostate gland disease and type 2 diabetes mellitus. RESULTS: ADR reports per investigated drug ranged from 2,400 to 50,000. The PRR-TA’s ability to detect true-positive SDRs (as acknowledged in approved labeling) was increased compared to the conventional PRR, and performed 8–31 % better than a recently proposed stricter EU-SDR definition. The PRR-TA removed false SDRs confounded by disease or disease spill-over by up to 63 %, while retaining/increasing the number of unclassified SDRs relevant for manual validation, and thereby improving the ratio between confounded SDRs (i.e., noise) and unclassified SDRs for all investigated drugs (possible signals). CONCLUSIONS: The performance of the PRR was improved by background restriction with the PRR-TA method; the number of false-positive SDRs decreased, and the ability to detect true-positive SDRs increased, improving the signal-to-noise ratio. Further development and validation of the method is needed within other TAs and databases, and for disproportionality analysis methods. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00228-014-1658-1) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2014-03-07 2014 /pmc/articles/PMC3978377/ /pubmed/24599513 http://dx.doi.org/10.1007/s00228-014-1658-1 Text en © The Author(s) 2014 https://creativecommons.org/licenses/by/4.0/ Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. |
spellingShingle | Pharmacoepidemiology and Prescription Grundmark, Birgitta Holmberg, Lars Garmo, Hans Zethelius, Björn Reducing the noise in signal detection of adverse drug reactions by standardizing the background: a pilot study on analyses of proportional reporting ratios-by-therapeutic area |
title | Reducing the noise in signal detection of adverse drug reactions by standardizing the background: a pilot study on analyses of proportional reporting ratios-by-therapeutic area |
title_full | Reducing the noise in signal detection of adverse drug reactions by standardizing the background: a pilot study on analyses of proportional reporting ratios-by-therapeutic area |
title_fullStr | Reducing the noise in signal detection of adverse drug reactions by standardizing the background: a pilot study on analyses of proportional reporting ratios-by-therapeutic area |
title_full_unstemmed | Reducing the noise in signal detection of adverse drug reactions by standardizing the background: a pilot study on analyses of proportional reporting ratios-by-therapeutic area |
title_short | Reducing the noise in signal detection of adverse drug reactions by standardizing the background: a pilot study on analyses of proportional reporting ratios-by-therapeutic area |
title_sort | reducing the noise in signal detection of adverse drug reactions by standardizing the background: a pilot study on analyses of proportional reporting ratios-by-therapeutic area |
topic | Pharmacoepidemiology and Prescription |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3978377/ https://www.ncbi.nlm.nih.gov/pubmed/24599513 http://dx.doi.org/10.1007/s00228-014-1658-1 |
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