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

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http://hdl.handle.net/10138/209591

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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

Title: Data management and data analysis techniques in pharmacoepidemiological studies using a pre-planned multi-database approach : a systematic literature review
Author: Bazelier, Marloes T.; Eriksson, Irene; de Vries, Frank; Schmidt, Marjanka K.; Raitanen, Jani; Haukka, Jari; Starup-Linde, Jakob; De Bruin, Marie L.; Andersen, Morten
Contributor: University of Helsinki, University of Helsinki
Date: 2015-09
Language: eng
Number of pages: 9
Belongs to series: Pharmacoepidemiology and Drug Safety
ISSN: 1053-8569
URI: http://hdl.handle.net/10138/209591
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.
Subject: pharmacoepidemiology
multi-database
systematic review
data management
analysis techniques
PERSISTENT PULMONARY-HYPERTENSION
SEROTONIN REUPTAKE INHIBITORS
SERIOUS CARDIOVASCULAR EVENTS
DOPAMINE AGONIST USE
PARKINSONS-DISEASE
RISK
PREGNANCY
DRUGS
HOSPITALIZATION
MEDICATIONS
317 Pharmacy
3142 Public health care science, environmental and occupational health
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