Practice-based evidence: profiling the safety of cilostazol by text-mining of clinical notes.

<h4>Background</h4>Peripheral arterial disease (PAD) is a growing problem with few available therapies. Cilostazol is the only FDA-approved medication with a class I indication for intermittent claudication, but carries a black box warning due to concerns for increased cardiovascular mor...

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Autores principales:	Nicholas J Leeper, Anna Bauer-Mehren, Srinivasan V Iyer, Paea Lependu, Cliff Olson, Nigam H Shah
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/c71709a69fe1404caaa92460471a83d8
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spelling	oai:doaj.org-article:c71709a69fe1404caaa92460471a83d82021-11-18T07:44:26ZPractice-based evidence: profiling the safety of cilostazol by text-mining of clinical notes.1932-620310.1371/journal.pone.0063499https://doaj.org/article/c71709a69fe1404caaa92460471a83d82013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23717437/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>Peripheral arterial disease (PAD) is a growing problem with few available therapies. Cilostazol is the only FDA-approved medication with a class I indication for intermittent claudication, but carries a black box warning due to concerns for increased cardiovascular mortality. To assess the validity of this black box warning, we employed a novel text-analytics pipeline to quantify the adverse events associated with Cilostazol use in a clinical setting, including patients with congestive heart failure (CHF).<h4>Methods and results</h4>We analyzed the electronic medical records of 1.8 million subjects from the Stanford clinical data warehouse spanning 18 years using a novel text-mining/statistical analytics pipeline. We identified 232 PAD patients taking Cilostazol and created a control group of 1,160 PAD patients not taking this drug using 1:5 propensity-score matching. Over a mean follow up of 4.2 years, we observed no association between Cilostazol use and any major adverse cardiovascular event including stroke (OR = 1.13, CI [0.82, 1.55]), myocardial infarction (OR = 1.00, CI [0.71, 1.39]), or death (OR = 0.86, CI [0.63, 1.18]). Cilostazol was not associated with an increase in any arrhythmic complication. We also identified a subset of CHF patients who were prescribed Cilostazol despite its black box warning, and found that it did not increase mortality in this high-risk group of patients.<h4>Conclusions</h4>This proof of principle study shows the potential of text-analytics to mine clinical data warehouses to uncover 'natural experiments' such as the use of Cilostazol in CHF patients. We envision this method will have broad applications for examining difficult to test clinical hypotheses and to aid in post-marketing drug safety surveillance. Moreover, our observations argue for a prospective study to examine the validity of a drug safety warning that may be unnecessarily limiting the use of an efficacious therapy.Nicholas J LeeperAnna Bauer-MehrenSrinivasan V IyerPaea LependuCliff OlsonNigam H ShahPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 5, p e63499 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Nicholas J Leeper Anna Bauer-Mehren Srinivasan V Iyer Paea Lependu Cliff Olson Nigam H Shah Practice-based evidence: profiling the safety of cilostazol by text-mining of clinical notes.
description	<h4>Background</h4>Peripheral arterial disease (PAD) is a growing problem with few available therapies. Cilostazol is the only FDA-approved medication with a class I indication for intermittent claudication, but carries a black box warning due to concerns for increased cardiovascular mortality. To assess the validity of this black box warning, we employed a novel text-analytics pipeline to quantify the adverse events associated with Cilostazol use in a clinical setting, including patients with congestive heart failure (CHF).<h4>Methods and results</h4>We analyzed the electronic medical records of 1.8 million subjects from the Stanford clinical data warehouse spanning 18 years using a novel text-mining/statistical analytics pipeline. We identified 232 PAD patients taking Cilostazol and created a control group of 1,160 PAD patients not taking this drug using 1:5 propensity-score matching. Over a mean follow up of 4.2 years, we observed no association between Cilostazol use and any major adverse cardiovascular event including stroke (OR = 1.13, CI [0.82, 1.55]), myocardial infarction (OR = 1.00, CI [0.71, 1.39]), or death (OR = 0.86, CI [0.63, 1.18]). Cilostazol was not associated with an increase in any arrhythmic complication. We also identified a subset of CHF patients who were prescribed Cilostazol despite its black box warning, and found that it did not increase mortality in this high-risk group of patients.<h4>Conclusions</h4>This proof of principle study shows the potential of text-analytics to mine clinical data warehouses to uncover 'natural experiments' such as the use of Cilostazol in CHF patients. We envision this method will have broad applications for examining difficult to test clinical hypotheses and to aid in post-marketing drug safety surveillance. Moreover, our observations argue for a prospective study to examine the validity of a drug safety warning that may be unnecessarily limiting the use of an efficacious therapy.
format	article
author	Nicholas J Leeper Anna Bauer-Mehren Srinivasan V Iyer Paea Lependu Cliff Olson Nigam H Shah
author_facet	Nicholas J Leeper Anna Bauer-Mehren Srinivasan V Iyer Paea Lependu Cliff Olson Nigam H Shah
author_sort	Nicholas J Leeper
title	Practice-based evidence: profiling the safety of cilostazol by text-mining of clinical notes.
title_short	Practice-based evidence: profiling the safety of cilostazol by text-mining of clinical notes.
title_full	Practice-based evidence: profiling the safety of cilostazol by text-mining of clinical notes.
title_fullStr	Practice-based evidence: profiling the safety of cilostazol by text-mining of clinical notes.
title_full_unstemmed	Practice-based evidence: profiling the safety of cilostazol by text-mining of clinical notes.
title_sort	practice-based evidence: profiling the safety of cilostazol by text-mining of clinical notes.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/c71709a69fe1404caaa92460471a83d8
work_keys_str_mv	AT nicholasjleeper practicebasedevidenceprofilingthesafetyofcilostazolbytextminingofclinicalnotes AT annabauermehren practicebasedevidenceprofilingthesafetyofcilostazolbytextminingofclinicalnotes AT srinivasanviyer practicebasedevidenceprofilingthesafetyofcilostazolbytextminingofclinicalnotes AT paealependu practicebasedevidenceprofilingthesafetyofcilostazolbytextminingofclinicalnotes AT cliffolson practicebasedevidenceprofilingthesafetyofcilostazolbytextminingofclinicalnotes AT nigamhshah practicebasedevidenceprofilingthesafetyofcilostazolbytextminingofclinicalnotes
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Practice-based evidence: profiling the safety of cilostazol by text-mining of clinical notes.

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