Cargando…

Web-Based Signal Detection Using Medical Forums Data in France: Comparative Analysis

BACKGROUND: While traditional signal detection methods in pharmacovigilance are based on spontaneous reports, the use of social media is emerging. The potential strength of Web-based data relies on their volume and real-time availability, allowing early detection of signals of disproportionate repor...

Descripción completa

Detalles Bibliográficos
Autores principales: Kürzinger, Marie-Laure, Schück, Stéphane, Texier, Nathalie, Abdellaoui, Redhouane, Faviez, Carole, Pouget, Julie, Zhang, Ling, Tcherny-Lessenot, Stéphanie, Lin, Stephen, Juhaeri, Juhaeri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6280030/
https://www.ncbi.nlm.nih.gov/pubmed/30459145
http://dx.doi.org/10.2196/10466
_version_ 1783378586982416384
author Kürzinger, Marie-Laure
Schück, Stéphane
Texier, Nathalie
Abdellaoui, Redhouane
Faviez, Carole
Pouget, Julie
Zhang, Ling
Tcherny-Lessenot, Stéphanie
Lin, Stephen
Juhaeri, Juhaeri
author_facet Kürzinger, Marie-Laure
Schück, Stéphane
Texier, Nathalie
Abdellaoui, Redhouane
Faviez, Carole
Pouget, Julie
Zhang, Ling
Tcherny-Lessenot, Stéphanie
Lin, Stephen
Juhaeri, Juhaeri
author_sort Kürzinger, Marie-Laure
collection PubMed
description BACKGROUND: While traditional signal detection methods in pharmacovigilance are based on spontaneous reports, the use of social media is emerging. The potential strength of Web-based data relies on their volume and real-time availability, allowing early detection of signals of disproportionate reporting (SDRs). OBJECTIVE: This study aimed (1) to assess the consistency of SDRs detected from patients’ medical forums in France compared with those detected from the traditional reporting systems and (2) to assess the ability of SDRs in identifying earlier than the traditional reporting systems. METHODS: Messages posted on patients’ forums between 2005 and 2015 were used. We retained 8 disproportionality definitions. Comparison of SDRs from the forums with SDRs detected in VigiBase was done by describing the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, receiver operating characteristics curve, and the area under the curve (AUC). The time difference in months between the detection dates of SDRs from the forums and VigiBase was provided. RESULTS: The comparison analysis showed that the sensitivity ranged from 29% to 50.6%, the specificity from 86.1% to 95.5%, the PPV from 51.2% to 75.4%, the NPV from 68.5% to 91.6%, and the accuracy from 68% to 87.7%. The AUC reached 0.85 when using the metric empirical Bayes geometric mean. Up to 38% (12/32) of the SDRs were detected earlier in the forums than that in VigiBase. CONCLUSIONS: The specificity, PPV, and NPV were high. The overall performance was good, showing that data from medical forums may be a valuable source for signal detection. In total, up to 38% (12/32) of the SDRs could have been detected earlier, thus, ensuring the increased safety of patients. Further enhancements are needed to investigate the reliability and validation of patients’ medical forums worldwide, the extension of this analysis to all possible drugs or at least to a wider selection of drugs, as well as to further assess performance against established signals.
format Online
Article
Text
id pubmed-6280030
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher JMIR Publications
record_format MEDLINE/PubMed
spelling pubmed-62800302019-01-03 Web-Based Signal Detection Using Medical Forums Data in France: Comparative Analysis Kürzinger, Marie-Laure Schück, Stéphane Texier, Nathalie Abdellaoui, Redhouane Faviez, Carole Pouget, Julie Zhang, Ling Tcherny-Lessenot, Stéphanie Lin, Stephen Juhaeri, Juhaeri J Med Internet Res Original Paper BACKGROUND: While traditional signal detection methods in pharmacovigilance are based on spontaneous reports, the use of social media is emerging. The potential strength of Web-based data relies on their volume and real-time availability, allowing early detection of signals of disproportionate reporting (SDRs). OBJECTIVE: This study aimed (1) to assess the consistency of SDRs detected from patients’ medical forums in France compared with those detected from the traditional reporting systems and (2) to assess the ability of SDRs in identifying earlier than the traditional reporting systems. METHODS: Messages posted on patients’ forums between 2005 and 2015 were used. We retained 8 disproportionality definitions. Comparison of SDRs from the forums with SDRs detected in VigiBase was done by describing the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, receiver operating characteristics curve, and the area under the curve (AUC). The time difference in months between the detection dates of SDRs from the forums and VigiBase was provided. RESULTS: The comparison analysis showed that the sensitivity ranged from 29% to 50.6%, the specificity from 86.1% to 95.5%, the PPV from 51.2% to 75.4%, the NPV from 68.5% to 91.6%, and the accuracy from 68% to 87.7%. The AUC reached 0.85 when using the metric empirical Bayes geometric mean. Up to 38% (12/32) of the SDRs were detected earlier in the forums than that in VigiBase. CONCLUSIONS: The specificity, PPV, and NPV were high. The overall performance was good, showing that data from medical forums may be a valuable source for signal detection. In total, up to 38% (12/32) of the SDRs could have been detected earlier, thus, ensuring the increased safety of patients. Further enhancements are needed to investigate the reliability and validation of patients’ medical forums worldwide, the extension of this analysis to all possible drugs or at least to a wider selection of drugs, as well as to further assess performance against established signals. JMIR Publications 2018-11-20 /pmc/articles/PMC6280030/ /pubmed/30459145 http://dx.doi.org/10.2196/10466 Text en ©Marie-Laure Kürzinger, Stéphane Schück, Nathalie Texier, Redhouane Abdellaoui, Carole Faviez, Julie Pouget, Ling Zhang, Stéphanie Tcherny-Lessenot, Stephen Lin, Juhaeri Juhaeri. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 20.11.2018. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Kürzinger, Marie-Laure
Schück, Stéphane
Texier, Nathalie
Abdellaoui, Redhouane
Faviez, Carole
Pouget, Julie
Zhang, Ling
Tcherny-Lessenot, Stéphanie
Lin, Stephen
Juhaeri, Juhaeri
Web-Based Signal Detection Using Medical Forums Data in France: Comparative Analysis
title Web-Based Signal Detection Using Medical Forums Data in France: Comparative Analysis
title_full Web-Based Signal Detection Using Medical Forums Data in France: Comparative Analysis
title_fullStr Web-Based Signal Detection Using Medical Forums Data in France: Comparative Analysis
title_full_unstemmed Web-Based Signal Detection Using Medical Forums Data in France: Comparative Analysis
title_short Web-Based Signal Detection Using Medical Forums Data in France: Comparative Analysis
title_sort web-based signal detection using medical forums data in france: comparative analysis
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6280030/
https://www.ncbi.nlm.nih.gov/pubmed/30459145
http://dx.doi.org/10.2196/10466
work_keys_str_mv AT kurzingermarielaure webbasedsignaldetectionusingmedicalforumsdatainfrancecomparativeanalysis
AT schuckstephane webbasedsignaldetectionusingmedicalforumsdatainfrancecomparativeanalysis
AT texiernathalie webbasedsignaldetectionusingmedicalforumsdatainfrancecomparativeanalysis
AT abdellaouiredhouane webbasedsignaldetectionusingmedicalforumsdatainfrancecomparativeanalysis
AT faviezcarole webbasedsignaldetectionusingmedicalforumsdatainfrancecomparativeanalysis
AT pougetjulie webbasedsignaldetectionusingmedicalforumsdatainfrancecomparativeanalysis
AT zhangling webbasedsignaldetectionusingmedicalforumsdatainfrancecomparativeanalysis
AT tchernylessenotstephanie webbasedsignaldetectionusingmedicalforumsdatainfrancecomparativeanalysis
AT linstephen webbasedsignaldetectionusingmedicalforumsdatainfrancecomparativeanalysis
AT juhaerijuhaeri webbasedsignaldetectionusingmedicalforumsdatainfrancecomparativeanalysis