Longitudinal medical records as a complement to routine drug safety signal analysis
Purpose To explore whether and how longitudinal medical records could be used as a source of reference in the early phases of signal detection and analysis of novel adverse drug reactions (ADRs) in a global pharmacovigilance database. Methods Drug and ADR combinations from the routine signal detecti...
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Veröffentlicht in: | Pharmacoepidemiology and drug safety 2015-05, Vol.24 (5), p.486-494 |
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creator | Star, Kristina Watson, Sarah Sandberg, Lovisa Johansson, Jeanette Edwards, I. Ralph |
description | Purpose
To explore whether and how longitudinal medical records could be used as a source of reference in the early phases of signal detection and analysis of novel adverse drug reactions (ADRs) in a global pharmacovigilance database.
Methods
Drug and ADR combinations from the routine signal detection process of VigiBase® in 2011 were matched to combinations in The Health Improvement Network (THIN). The number and type of drugs and ADRs from the data sets were investigated. For unlabelled combinations, graphical display of longitudinal event patterns (chronographs) in THIN was inspected to determine if the pattern supported the VigiBase combination.
Results
Of 458 combinations in the VigiBase data set, 190 matched to corresponding combinations in THIN (after excluding drugs with less than 100 prescriptions in THIN). Eighteen percent of the VigiBase and 9% of the matched THIN combinations referred to new drugs reported with serious reactions. Of the 112 unlabelled combinations matched to THIN, 52 chronographs were inconclusive mainly because of lack of data; 34 lacked any outstanding pattern around the time of prescription; 24 had an elevation of events in the pre‐prescription period, hence weakened the suspicion of a drug relationship; two had an elevated pattern of events exclusively in the post‐prescription period that, after review of individual patient histories, did not support an association.
Conclusions
Longitudinal medical records were useful in understanding the clinical context around a drug and suspected ADR combination and the probability of a causal relationship. A drawback was the paucity of data for newly marketed drugs with serious reactions. © 2015 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd. |
doi_str_mv | 10.1002/pds.3739 |
format | Article |
fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5024044</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3662711291</sourcerecordid><originalsourceid>FETCH-LOGICAL-c5469-3a55286986d041a72a91da49ee991449430042c6a68a966f97a31afe0bd315cf3</originalsourceid><addsrcrecordid>eNp1kF1LwzAUhoMoOqfgL5CCN950njQfbW4E8RuGipu4uxDbdGZ2zUxadf_ejM2hF0LIOXCevOfNi9ABhh4GSE5mhe-RlIgN1MEgRIwZSzcXPSNxxrjYQbveTwDCTNBttJMwnhCgrIMGfVuPTdMWplZVNNWFyUN1Oreu8JEKJ8rtdFbpqa6bqLGRs21jah0Vrh1HXpW6mUfejBevVbjm3vg9tFWqyuv9Ve2ip6vL4flN3L-_vj0_68c5o1zERDGWZFxkvACKVZoogQtFhdZCYEoFJQA0ybnimRKclyJVBIeF8FIQzPKSdNHpUnfWvgTneXDoVCVnzkyVm0urjPw7qc2rHNsPySChQGkQOFoJOPveat_IiW1d-IWXmKdUYMiAB-p4SeXOeu90ud6AQS7ilyF-uYg_oIe_Ha3Bn7wDEC-BT1Pp-b9C8uFisBJc8cY3-mvNK_cmeUpSJp_vriUMR2l_NHiUCfkGtReejA</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1674910806</pqid></control><display><type>article</type><title>Longitudinal medical records as a complement to routine drug safety signal analysis</title><source>MEDLINE</source><source>Wiley Online Library All Journals</source><creator>Star, Kristina ; Watson, Sarah ; Sandberg, Lovisa ; Johansson, Jeanette ; Edwards, I. Ralph</creator><creatorcontrib>Star, Kristina ; Watson, Sarah ; Sandberg, Lovisa ; Johansson, Jeanette ; Edwards, I. Ralph</creatorcontrib><description>Purpose
To explore whether and how longitudinal medical records could be used as a source of reference in the early phases of signal detection and analysis of novel adverse drug reactions (ADRs) in a global pharmacovigilance database.
Methods
Drug and ADR combinations from the routine signal detection process of VigiBase® in 2011 were matched to combinations in The Health Improvement Network (THIN). The number and type of drugs and ADRs from the data sets were investigated. For unlabelled combinations, graphical display of longitudinal event patterns (chronographs) in THIN was inspected to determine if the pattern supported the VigiBase combination.
Results
Of 458 combinations in the VigiBase data set, 190 matched to corresponding combinations in THIN (after excluding drugs with less than 100 prescriptions in THIN). Eighteen percent of the VigiBase and 9% of the matched THIN combinations referred to new drugs reported with serious reactions. Of the 112 unlabelled combinations matched to THIN, 52 chronographs were inconclusive mainly because of lack of data; 34 lacked any outstanding pattern around the time of prescription; 24 had an elevation of events in the pre‐prescription period, hence weakened the suspicion of a drug relationship; two had an elevated pattern of events exclusively in the post‐prescription period that, after review of individual patient histories, did not support an association.
Conclusions
Longitudinal medical records were useful in understanding the clinical context around a drug and suspected ADR combination and the probability of a causal relationship. A drawback was the paucity of data for newly marketed drugs with serious reactions. © 2015 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd.</description><identifier>ISSN: 1053-8569</identifier><identifier>EISSN: 1099-1557</identifier><identifier>DOI: 10.1002/pds.3739</identifier><identifier>PMID: 25623045</identifier><language>eng</language><publisher>England: Blackwell Publishing Ltd</publisher><subject>Adverse Drug Reaction Reporting Systems - organization & administration ; Adverse Drug Reaction Reporting Systems - statistics & numerical data ; adverse drug reactions ; Databases, Factual ; Drug-Related Side Effects and Adverse Reactions - epidemiology ; Drug-Related Side Effects and Adverse Reactions - etiology ; Drugs ; Electronic Health Records - statistics & numerical data ; electronic medical records ; Humans ; individual case safety reports ; Longitudinal Studies ; Medical records ; Original Report ; Original Reports ; pharmacoepidemiology ; Pharmacology ; Pharmacovigilance ; post-marketing surveillance ; Safety ; Side effects ; signal detection and analysis ; temporal pattern discovery</subject><ispartof>Pharmacoepidemiology and drug safety, 2015-05, Vol.24 (5), p.486-494</ispartof><rights>2015 The Authors. published by John Wiley & Sons, Ltd.</rights><rights>2015 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd.</rights><rights>Copyright © 2015 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5469-3a55286986d041a72a91da49ee991449430042c6a68a966f97a31afe0bd315cf3</citedby><cites>FETCH-LOGICAL-c5469-3a55286986d041a72a91da49ee991449430042c6a68a966f97a31afe0bd315cf3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fpds.3739$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fpds.3739$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,1416,27923,27924,45573,45574</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25623045$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Star, Kristina</creatorcontrib><creatorcontrib>Watson, Sarah</creatorcontrib><creatorcontrib>Sandberg, Lovisa</creatorcontrib><creatorcontrib>Johansson, Jeanette</creatorcontrib><creatorcontrib>Edwards, I. Ralph</creatorcontrib><title>Longitudinal medical records as a complement to routine drug safety signal analysis</title><title>Pharmacoepidemiology and drug safety</title><addtitle>Pharmacoepidemiol Drug Saf</addtitle><description>Purpose
To explore whether and how longitudinal medical records could be used as a source of reference in the early phases of signal detection and analysis of novel adverse drug reactions (ADRs) in a global pharmacovigilance database.
Methods
Drug and ADR combinations from the routine signal detection process of VigiBase® in 2011 were matched to combinations in The Health Improvement Network (THIN). The number and type of drugs and ADRs from the data sets were investigated. For unlabelled combinations, graphical display of longitudinal event patterns (chronographs) in THIN was inspected to determine if the pattern supported the VigiBase combination.
Results
Of 458 combinations in the VigiBase data set, 190 matched to corresponding combinations in THIN (after excluding drugs with less than 100 prescriptions in THIN). Eighteen percent of the VigiBase and 9% of the matched THIN combinations referred to new drugs reported with serious reactions. Of the 112 unlabelled combinations matched to THIN, 52 chronographs were inconclusive mainly because of lack of data; 34 lacked any outstanding pattern around the time of prescription; 24 had an elevation of events in the pre‐prescription period, hence weakened the suspicion of a drug relationship; two had an elevated pattern of events exclusively in the post‐prescription period that, after review of individual patient histories, did not support an association.
Conclusions
Longitudinal medical records were useful in understanding the clinical context around a drug and suspected ADR combination and the probability of a causal relationship. A drawback was the paucity of data for newly marketed drugs with serious reactions. © 2015 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd.</description><subject>Adverse Drug Reaction Reporting Systems - organization & administration</subject><subject>Adverse Drug Reaction Reporting Systems - statistics & numerical data</subject><subject>adverse drug reactions</subject><subject>Databases, Factual</subject><subject>Drug-Related Side Effects and Adverse Reactions - epidemiology</subject><subject>Drug-Related Side Effects and Adverse Reactions - etiology</subject><subject>Drugs</subject><subject>Electronic Health Records - statistics & numerical data</subject><subject>electronic medical records</subject><subject>Humans</subject><subject>individual case safety reports</subject><subject>Longitudinal Studies</subject><subject>Medical records</subject><subject>Original Report</subject><subject>Original Reports</subject><subject>pharmacoepidemiology</subject><subject>Pharmacology</subject><subject>Pharmacovigilance</subject><subject>post-marketing surveillance</subject><subject>Safety</subject><subject>Side effects</subject><subject>signal detection and analysis</subject><subject>temporal pattern discovery</subject><issn>1053-8569</issn><issn>1099-1557</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>EIF</sourceid><recordid>eNp1kF1LwzAUhoMoOqfgL5CCN950njQfbW4E8RuGipu4uxDbdGZ2zUxadf_ejM2hF0LIOXCevOfNi9ABhh4GSE5mhe-RlIgN1MEgRIwZSzcXPSNxxrjYQbveTwDCTNBttJMwnhCgrIMGfVuPTdMWplZVNNWFyUN1Oreu8JEKJ8rtdFbpqa6bqLGRs21jah0Vrh1HXpW6mUfejBevVbjm3vg9tFWqyuv9Ve2ip6vL4flN3L-_vj0_68c5o1zERDGWZFxkvACKVZoogQtFhdZCYEoFJQA0ybnimRKclyJVBIeF8FIQzPKSdNHpUnfWvgTneXDoVCVnzkyVm0urjPw7qc2rHNsPySChQGkQOFoJOPveat_IiW1d-IWXmKdUYMiAB-p4SeXOeu90ud6AQS7ilyF-uYg_oIe_Ha3Bn7wDEC-BT1Pp-b9C8uFisBJc8cY3-mvNK_cmeUpSJp_vriUMR2l_NHiUCfkGtReejA</recordid><startdate>201505</startdate><enddate>201505</enddate><creator>Star, Kristina</creator><creator>Watson, Sarah</creator><creator>Sandberg, Lovisa</creator><creator>Johansson, Jeanette</creator><creator>Edwards, I. Ralph</creator><general>Blackwell Publishing Ltd</general><general>Wiley Subscription Services, Inc</general><general>John Wiley and Sons Inc</general><scope>BSCLL</scope><scope>24P</scope><scope>WIN</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TK</scope><scope>K9.</scope><scope>5PM</scope></search><sort><creationdate>201505</creationdate><title>Longitudinal medical records as a complement to routine drug safety signal analysis</title><author>Star, Kristina ; Watson, Sarah ; Sandberg, Lovisa ; Johansson, Jeanette ; Edwards, I. Ralph</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5469-3a55286986d041a72a91da49ee991449430042c6a68a966f97a31afe0bd315cf3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Adverse Drug Reaction Reporting Systems - organization & administration</topic><topic>Adverse Drug Reaction Reporting Systems - statistics & numerical data</topic><topic>adverse drug reactions</topic><topic>Databases, Factual</topic><topic>Drug-Related Side Effects and Adverse Reactions - epidemiology</topic><topic>Drug-Related Side Effects and Adverse Reactions - etiology</topic><topic>Drugs</topic><topic>Electronic Health Records - statistics & numerical data</topic><topic>electronic medical records</topic><topic>Humans</topic><topic>individual case safety reports</topic><topic>Longitudinal Studies</topic><topic>Medical records</topic><topic>Original Report</topic><topic>Original Reports</topic><topic>pharmacoepidemiology</topic><topic>Pharmacology</topic><topic>Pharmacovigilance</topic><topic>post-marketing surveillance</topic><topic>Safety</topic><topic>Side effects</topic><topic>signal detection and analysis</topic><topic>temporal pattern discovery</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Star, Kristina</creatorcontrib><creatorcontrib>Watson, Sarah</creatorcontrib><creatorcontrib>Sandberg, Lovisa</creatorcontrib><creatorcontrib>Johansson, Jeanette</creatorcontrib><creatorcontrib>Edwards, I. Ralph</creatorcontrib><collection>Istex</collection><collection>Wiley-Blackwell Open Access Titles</collection><collection>Wiley Free Content</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Neurosciences Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Pharmacoepidemiology and drug safety</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Star, Kristina</au><au>Watson, Sarah</au><au>Sandberg, Lovisa</au><au>Johansson, Jeanette</au><au>Edwards, I. Ralph</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Longitudinal medical records as a complement to routine drug safety signal analysis</atitle><jtitle>Pharmacoepidemiology and drug safety</jtitle><addtitle>Pharmacoepidemiol Drug Saf</addtitle><date>2015-05</date><risdate>2015</risdate><volume>24</volume><issue>5</issue><spage>486</spage><epage>494</epage><pages>486-494</pages><issn>1053-8569</issn><eissn>1099-1557</eissn><abstract>Purpose
To explore whether and how longitudinal medical records could be used as a source of reference in the early phases of signal detection and analysis of novel adverse drug reactions (ADRs) in a global pharmacovigilance database.
Methods
Drug and ADR combinations from the routine signal detection process of VigiBase® in 2011 were matched to combinations in The Health Improvement Network (THIN). The number and type of drugs and ADRs from the data sets were investigated. For unlabelled combinations, graphical display of longitudinal event patterns (chronographs) in THIN was inspected to determine if the pattern supported the VigiBase combination.
Results
Of 458 combinations in the VigiBase data set, 190 matched to corresponding combinations in THIN (after excluding drugs with less than 100 prescriptions in THIN). Eighteen percent of the VigiBase and 9% of the matched THIN combinations referred to new drugs reported with serious reactions. Of the 112 unlabelled combinations matched to THIN, 52 chronographs were inconclusive mainly because of lack of data; 34 lacked any outstanding pattern around the time of prescription; 24 had an elevation of events in the pre‐prescription period, hence weakened the suspicion of a drug relationship; two had an elevated pattern of events exclusively in the post‐prescription period that, after review of individual patient histories, did not support an association.
Conclusions
Longitudinal medical records were useful in understanding the clinical context around a drug and suspected ADR combination and the probability of a causal relationship. A drawback was the paucity of data for newly marketed drugs with serious reactions. © 2015 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd.</abstract><cop>England</cop><pub>Blackwell Publishing Ltd</pub><pmid>25623045</pmid><doi>10.1002/pds.3739</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adverse Drug Reaction Reporting Systems - organization & administration Adverse Drug Reaction Reporting Systems - statistics & numerical data adverse drug reactions Databases, Factual Drug-Related Side Effects and Adverse Reactions - epidemiology Drug-Related Side Effects and Adverse Reactions - etiology Drugs Electronic Health Records - statistics & numerical data electronic medical records Humans individual case safety reports Longitudinal Studies Medical records Original Report Original Reports pharmacoepidemiology Pharmacology Pharmacovigilance post-marketing surveillance Safety Side effects signal detection and analysis temporal pattern discovery |
title | Longitudinal medical records as a complement to routine drug safety signal analysis |
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