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Ranking Adverse Drug Reactions With Crowdsourcing

BACKGROUND: There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used...

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Autores principales: Gottlieb, Assaf, Hoehndorf, Robert, Dumontier, Michel, Altman, Russ B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications Inc. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4387295/
https://www.ncbi.nlm.nih.gov/pubmed/25800813
http://dx.doi.org/10.2196/jmir.3962
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author Gottlieb, Assaf
Hoehndorf, Robert
Dumontier, Michel
Altman, Russ B
author_facet Gottlieb, Assaf
Hoehndorf, Robert
Dumontier, Michel
Altman, Russ B
author_sort Gottlieb, Assaf
collection PubMed
description BACKGROUND: There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. OBJECTIVE: The intent of the study was to rank ADRs according to severity. METHODS: We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. RESULTS: There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. CONCLUSIONS: ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.
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spelling pubmed-43872952015-04-10 Ranking Adverse Drug Reactions With Crowdsourcing Gottlieb, Assaf Hoehndorf, Robert Dumontier, Michel Altman, Russ B J Med Internet Res Original Paper BACKGROUND: There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. OBJECTIVE: The intent of the study was to rank ADRs according to severity. METHODS: We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. RESULTS: There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. CONCLUSIONS: ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making. JMIR Publications Inc. 2015-03-23 /pmc/articles/PMC4387295/ /pubmed/25800813 http://dx.doi.org/10.2196/jmir.3962 Text en ©Assaf Gottlieb, Robert Hoehndorf, Michel Dumontier, Russ B Altman. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 23.03.2015. http://creativecommons.org/licenses/by/2.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), 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
Gottlieb, Assaf
Hoehndorf, Robert
Dumontier, Michel
Altman, Russ B
Ranking Adverse Drug Reactions With Crowdsourcing
title Ranking Adverse Drug Reactions With Crowdsourcing
title_full Ranking Adverse Drug Reactions With Crowdsourcing
title_fullStr Ranking Adverse Drug Reactions With Crowdsourcing
title_full_unstemmed Ranking Adverse Drug Reactions With Crowdsourcing
title_short Ranking Adverse Drug Reactions With Crowdsourcing
title_sort ranking adverse drug reactions with crowdsourcing
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4387295/
https://www.ncbi.nlm.nih.gov/pubmed/25800813
http://dx.doi.org/10.2196/jmir.3962
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