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

被引:16
作者
Bazelier, Marloes T. [1 ]
Eriksson, Irene [2 ]
de Vries, Frank [1 ,3 ]
Schmidt, Marjanka K. [4 ]
Raitanen, Jani [5 ,6 ]
Haukka, Jari [7 ]
Starup-Linde, Jakob [8 ,9 ]
De Bruin, Marie L. [1 ]
Andersen, Morten [2 ]
机构
[1] Univ Utrecht, Utrecht Inst Pharmaceut Sci, Dept Pharmacoepidemiol & Clin Pharmacol, NL-3584 CG Utrecht, Netherlands
[2] Karolinska Inst, Ctr Pharmacoepidemiol, Stockholm, Sweden
[3] Maastricht Univ, Med Ctr, Department Clin Pharm & Toxicol, Maastricht, Netherlands
[4] Netherlands Canc Inst, Div Mol Pathol, Amsterdam, Netherlands
[5] Univ Tampere, Sch Hlth Sci, FIN-33101 Tampere, Finland
[6] UKK Inst Hlth Promot, Tampere, Finland
[7] Univ Helsinki, Helsinki, Finland
[8] Aalborg Univ, Aalborg, Denmark
[9] Aarhus Univ Hosp, Dept Endocrinol & Internal Med, DK-8000 Aarhus, Denmark
关键词
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;
D O I
10.1002/pds.3828
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
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.
引用
收藏
页码:897 / 905
页数:9
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