Data management and data analysis techniques in pharmacoepidemiological studies using a pre-planned multi-database approach : a systematic literature review

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dc.contributor.author Bazelier, Marloes T.
dc.contributor.author Eriksson, Irene
dc.contributor.author de Vries, Frank
dc.contributor.author Schmidt, Marjanka K.
dc.contributor.author Raitanen, Jani
dc.contributor.author Haukka, Jari
dc.contributor.author Starup-Linde, Jakob
dc.contributor.author De Bruin, Marie L.
dc.contributor.author Andersen, Morten
dc.date.accessioned 2017-08-10T12:10:00Z
dc.date.available 2017-08-10T12:10:00Z
dc.date.issued 2015-09
dc.identifier.citation Bazelier , M T , Eriksson , I , de Vries , F , Schmidt , M K , Raitanen , J , Haukka , J , Starup-Linde , J , De Bruin , M L & Andersen , M 2015 , ' Data management and data analysis techniques in pharmacoepidemiological studies using a pre-planned multi-database approach : a systematic literature review ' , Pharmacoepidemiology and Drug Safety , vol. 24 , no. 9 , pp. 897-905 . https://doi.org/10.1002/pds.3828
dc.identifier.other PURE: 54096250
dc.identifier.other PURE UUID: c9e4e3e2-8b17-4b8d-84eb-c6b7f96e06c6
dc.identifier.other WOS: 000360764300001
dc.identifier.other Scopus: 84940930388
dc.identifier.other ORCID: /0000-0003-1450-6208/work/29640014
dc.identifier.uri http://hdl.handle.net/10138/209591
dc.description.abstract PurposeTo identify pharmacoepidemiological multi-database studies and to describe data management and data analysis techniques used for combining data. MethodsSystematic literature searches were conducted in PubMed and Embase complemented by a manual literature search. We included pharmacoepidemiological multi-database studies published from 2007 onwards that combined data for a pre-planned common analysis or quantitative synthesis. Information was retrieved about study characteristics, methods used for individual-level analyses and meta-analyses, data management and motivations for performing the study. ResultsWe found 3083 articles by the systematic searches and an additional 176 by the manual search. After full-text screening of 75 articles, 22 were selected for final inclusion. The number of databases used per study ranged from 2 to 17 (median=4.0). Most studies used a cohort design (82%) instead of a case-control design (18%). Logistic regression was most often used for individual-level analyses (41%), followed by Cox regression (23%) and Poisson regression (14%). As meta-analysis method, a majority of the studies combined individual patient data (73%). Six studies performed an aggregate meta-analysis (27%), while a semi-aggregate approach was applied in three studies (14%). Information on central programming or heterogeneity assessment was missing in approximately half of the publications. Most studies were motivated by improving power (86%). ConclusionsPharmacoepidemiological multi-database studies are a well-powered strategy to address safety issues and have increased in popularity. To be able to correctly interpret the results of these studies, it is important to systematically report on database management and analysis techniques, including central programming and heterogeneity testing. (c) 2015 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd. en
dc.format.extent 9
dc.language.iso eng
dc.relation.ispartof Pharmacoepidemiology and Drug Safety
dc.rights cc_by_nc_nd
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject pharmacoepidemiology
dc.subject multi-database
dc.subject systematic review
dc.subject data management
dc.subject analysis techniques
dc.subject PERSISTENT PULMONARY-HYPERTENSION
dc.subject SEROTONIN REUPTAKE INHIBITORS
dc.subject SERIOUS CARDIOVASCULAR EVENTS
dc.subject DOPAMINE AGONIST USE
dc.subject PARKINSONS-DISEASE
dc.subject RISK
dc.subject PREGNANCY
dc.subject DRUGS
dc.subject HOSPITALIZATION
dc.subject MEDICATIONS
dc.subject 317 Pharmacy
dc.subject 3142 Public health care science, environmental and occupational health
dc.title Data management and data analysis techniques in pharmacoepidemiological studies using a pre-planned multi-database approach : a systematic literature review en
dc.type Review Article
dc.contributor.organization University of Helsinki
dc.contributor.organization Clinicum
dc.contributor.organization Jari Haukka / Principal Investigator
dc.contributor.organization Department of Public Health
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.1002/pds.3828
dc.relation.issn 1053-8569
dc.rights.accesslevel openAccess
dc.type.version publishedVersion

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