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

Abstract

PURPOSE: To identify pharmacoepidemiological multi-database studies and to describe data management and data analysis techniques used for combining data. METHODS: Systematic 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. RESULTS: We 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%). CONCLUSIONS: Pharmacoepidemiological 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.

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

Author: Bazelier, Maroles T,Eriksson, Irene,de Vries, Frank,Schmidt, Marjanka K,Raitanen, Jani,Haukka, Jari,Starup-Linde, Jacob,De Bruin, Marie,Andersen, Morten
Year: 2015
Source: https://trepo.tuni.fi/bitstream/10024/100158/1/data_management_and_data_2015.pdf
REVIEW
Da a managemen and da a analysis echniques in
pha macoepidemiological s udies using a p e-planned
mul i-da abase app oach: a sys ema ic li e a u e e iew
†
Ma loes T. Bazelie
1
*, I ene E iksson
2
, F ank de V ies
1,3
, Ma janka K. Schmid
4
, Jani Rai anen
5,6
, Ja i Haukka
7
,
Jakob S a up-Linde
8,9
, Ma ie L. De B uin
1
and Mo en Ande sen
2
1
Di ision o Pha macoepidemiology and Clinical Pha macology, U ech Ins i u e o Pha maceu ical Sciences, U ech Uni e si y, Ne he lands
2
Cen e o Pha macoepidemiology, Ka olinska Ins i u e , S ockholm, Sweden
3
Depa men o Clinical Pha macy and Toxicology, Maas ich Uni e si y Medical Cen e, Maas ich , Ne he lands
4
Di ision o Molecula Pa hology, Ne he lands Cance Ins i u e, Ne he lands
5
School o Heal h Sciences, Uni e si y o Tampe e, Finland
6
UKK Ins i u e o Heal h P omo ion, Tampe e, Finland
7
Uni e si y o Helsinki, Helsinki, Finland
8
Aalbo g Uni e si y, Aalbo g, Denma k
9
Depa men o Endoc inology and In e nal Medicine, Aa hus Uni e si y Hospi al, Aa hus, Denma k
ABSTRACT
Pu pose To iden i y pha macoepidemiological mul i-da abase s udies and o desc ibe da a managemen and da a analysis echniques used
o combining da a.
Me hods Sys ema ic li e a u e sea ches we e conduc ed in PubMed and Embase complemen ed by a manual li e a u e sea ch. We included
pha macoepidemiological mul i-da abase s udies published om 2007 onwa ds ha combined da a o a p e-planned common analysis o
quan i a i e syn hesis. In o ma ion was e ie ed abou s udy cha ac e is ics, me hods used o indi idual-le el analyses and me a-
analyses, da a managemen and mo i a ions o pe o ming he s udy.
Resul s We ound 3083 a icles by he sys ema ic sea ches and an addi ional 176 by he manual sea ch. A e ull- ex sc eening o 75 a icles, 22
we e selec ed o final inclusion. The numbe o da abases used pe s udy anged om 2 o 17 (median = 4.0). Mos s udies used a coho design
(82%) ins ead o a case–con ol design (18%). Logis ic eg ession was mos o en used o indi idual-le el analyses (41%), ollowed by Cox eg es-
sion (23%) and Poisson eg ession (14%). As me a-analysis me hod, a majo i y o he s udies combined indi idual pa ien da a (73%). Six s udies
pe o med an agg ega e me a-analysis (27%), while a semi-agg ega e app oach was applied in h ee s udies (14%). In o ma ion on cen al p og am-
ming o he e ogenei y assessmen was missing in app oxima ely hal o he publica ions. Mos s udies we e mo i a ed by imp o ing powe (86%).
Conclusions Pha macoepidemiological mul i-da abase s udies a e a well-powe ed s a egy o add ess sa e y issues and ha e inc eased
in popula i y. To be able o co ec ly in e p e he esul s o hese s udies, i is impo an o sys ema ically epo on da abase managemen
and analysis echniques, including cen al p og amming and he e ogenei y es ing. © 2015 The Au ho s. Pha macoepidemiology and
D ug Sa e y published by John Wiley & Sons, L d.
key wo ds—pha macoepidemiology; mul i-da abase; sys ema ic e iew; da a managemen ; analysis echniques
Recei ed 18 Decembe 2014; Re ised 29 May 2015; Accep ed 08 June 2015
INTRODUCTION
The need o pos -app o al su eillance o d ug sa e y
has been widely ecognized o mo e han ou decades.
F om he ea ly days o pha macoepidemiology, ini ia-
i es ha e been unde aken o s udy sa e y and, mos e-
cen ly, e ec i eness o medica ions using ou inely
collec ed heal hca e da a. O e he pas decade, an
inc easing numbe o s udies ha e been pe o med using
heal hca e da abases om mul iple coun ies, egions o
*Co espondence o: M. T. Bazelie , Depa men o Pha macoepidemiology and
Clinical Pha macology, U ech Ins i u e o Pha maceu ical Sciences,
U ech Uni e si y, Uni e si ei sweg 99, 3584 CG U ech , Ne he lands. E-mail:
[email p o ec ed]
†
P io pos ings and p esen a ions: Some findings om his s udy we e p esen ed
a he ICPE con e ence 2014 du ing he wo kshop ‘The Common Da a Model:
Lessons om Pas P ojec s and Ongoing Ini ia i es’(Pha macoepidemiol D ug
Sa . 2014 Oc ; 23 Suppl 1: 361).
© 2015 The Au ho s. Pha macoepidemiology and D ug Sa e y published by John Wiley & Sons, L d.
pha macoepidemiology and d ug sa e y 2015; 24: 897–905
Published online 14 July 2015 in Wiley Online Lib a y (wileyonlinelib a y.com) DOI: 10.1002/pds.3828
This is an open access a icle unde he e ms o he C ea i e Commons A ibu ion-NonComme cial-NoDe i s License, which pe mi s use
and dis ibu ion in any medium, p o ided he o iginal wo k is p ope ly ci ed, he use is non-comme cial and no modifica ions o adap a ions
a e made.
heal hca e o ganiza ions. Using da a om mul iple da a-
bases o e s a numbe o po en ial ad an ages such as in-
c eased sample size (da ase s become la ge enough o
gi e p ecise es ima es o medica ion isks and benefi s
e en o a e ou comes and exposu es) and gene aliz-
abili y (when simila esul s a e ound in s udies u ilizing
he same me hodology in he e ogeneous popula ions).
Fu he mo e, i o e s a po en ial o using a s anda d-
ized me hodological app oach ac oss da a sou ces.
A numbe o la ge ini ia i es ha e been launched o
de elop me hods o combining da a om mul iple
da abases and egis e s. In he Uni ed S a es (U.S.),
he Obse a ional Medical Ou comes Pa ne ship
(OMOP)
1
and he Mini-Sen inel p og am
2
ha e been
un since 2007 and 2008, espec i ely. Da a a e o en
combined using he heal h main enance o ganiza ion
(HMO) Resea ch Ne wo k, a conso ium o 19 la ge
heal hca e deli e y o ganiza ions in he U.S.
3
The Ca-
nadian Ne wo k o Obse a ional D ug E ec S udies
(CNODES), a dis ibu ed ne wo k o Canadian e-
sea che s and da a cen e s, was launched in 2011.
4,5
Eu opean ini ia i es ha add ess logis ical and me h-
odological p oblems o conduc ing mul i-da abase
s udies include EU-ADR
6
and IMI-PROTECT.
7
Recen ly, he Asian Pha macoepidemiology Ne wo k
(AsPEN),
8
a collabo a ion including Asian coun ies,
was also s a ed. Besides hese la ge p og ams, a hand-
ul o smalle esea ch p ojec s ha e also combined da a
om se e al heal hca e da abases.
9–13
The e a e a ious ways o combine da a om se -
e al independen da abases, which all ha e di e en
ad an ages and disad an ages. A combina ion o ag-
g ega e esul s does no equi e sha ing o indi idual
pa ien da a and makes op imal use o locally a ailable
da a (e.g. in o ma ion on con ounde s). Howe e ,
co ec ing o he e ogenei y be ween he da abases
may no be ully possible when combining summa y
es ima es. A combina ion o indi idual pa ien da a
opens mo e space o explo ing and co ec ing o he -
e ogenei y; i o e s an oppo uni y o use exac ly he
same defini ions o exposu es, ou comes, co a ia es,
and ime windows. This app oach may, howe e , e-
sul in a comp omise when ele an in o ma ion is los
i no a ailable in all da abases (possibly leading o
la ge esidual con ounding).
To ou knowledge, no sys ema ic e iew has been
pe o med ye o selec mul i-da abase s udies and o
illumina e which me hods ha e mos equen ly been
used o combine da a. Ou aim was he e o e o iden-
i y pha macoepidemiological s udies using a p e-
planned mul i-da abase app oach and o desc ibe da a
managemen and da a analysis echniques used o
combining da a.
METHODS
Li e a u e sea ch
We conduc ed sys ema ic li e a u e sea ches in
PubMed and Embase, as well as a manual li e a u e
sea ch, o iden i y ele an mul i-da abase obse a-
ional s udies. We ollowed he PRISMA guideline
(www.p isma-s a emen .o g).
The ollowing inclusion c i e ia we e applied: (i)
pee - e iewed pha macoepidemiological s udy (de-
fined as an obse a ional s udy abou he sa e y o e -
ec i eness o medica ion); (ii) published om 2007
onwa ds; (iii) s udy subjec s we e selec ed om wo
o mo e independen heal hca e da abases (i.e. da a-
bases co e ing a di e en s udy popula ion); (i ) all
da abases wi hin he s udy we e analyzed o answe
he same esea ch ques ion; and ( ) da a we e com-
bined o a p e-planned common analysis o quan i a-
i e syn hesis (i.e. da a we e combined ei he a
indi idual pa ien -le el o he es ima es ob ained om
indi idual da abases we e combined in analyses). We
excluded d ug u iliza ion s udies, a icles ha ocused
on he de ec ion o ad e se d ug eac ions (ADRs)
and o he pha maco igilance s udies, s udies ha only
epo ed esul s om sepa a e da abases wi hou p o-
iding any combined es ima es, pu ely me hodological
pape s (e.g. desc ibing me hods o combine da a, bu
no ac ually doing so in he pape ), as well as s udies
published in languages o he han English (exclusion
c i e ia we e applied sequen ially).
Sys ema ic sea ch s a egies o PubMed and
Embase we e de eloped unde he supe ision o a e-
sea ch lib a ian and included ex wo ds and ele an
indexing o cap u e pha macoepidemiological s udies
sa is ying he inclusion c i e ia. The s a egies we e
adap ed o ma ch he s uc u e o each da abase and
we e based on sea ch e ms ha included ‘d ugs’,‘da-
abases’, and ‘epidemiology’/‘obse a ional s udies’
(using MeSH, Em ee, and ee ex e ms); bo h da a-
bases we e sea ched om 2007 o Oc obe 2013 (see
e- ables 1 and 2 o he ull sea ch s a egy in Pubmed
and Embase, espec i ely). The da e fil e om 2007
onwa ds was applied as ou pilo sea ches did no
iden i y any ele an publica ions be o e 2007. We
he e o e belie ed ha i would help imp o e he p e-
cision o he sea ch wi hou nega i e impac on i s sen-
si i i y. One au ho (IE) sc eened he i les and
abs ac s o he iden ified a icles using ou inclusion
and exclusion c i e ia o selec a icles eligible o
ull- ex sc eening.
The elec onic li e a u e sea ch was supplemen ed
wi h a manual sea ch (2007 o Decembe 2013). We
iden ified publica ions lis ed on he ollowing esea ch
m. . bazelie
e al.
898
© 2015 The Au ho s. Pha macoepidemiology and D ug Sa e y
published by John Wiley & Sons, L d.
Pha macoepidemiology and D ug Sa e y, 2015; 24: 897–905
DOI: 10.1002/pds
p ojec s’websi es: (i) OMOP (h p://omop. nih.o g
and www.omop.o g); (ii) Mini-Sen inel (www.mini-
sen inel.o g); (iii) he HMO Resea ch Ne wo k
(www.hmo esea chne wo k.o g); (i ) EU-ADR (www.
euad -p ojec .o g); ( ) IMI-PROTECT (www.imi-p o-
ec .eu); ( i) AsPEN (www.aspenne .asia); and ( ii)
CNODES (www.cnodes.ca). In addi ion, esea che s
wi hin ou eam we e consul ed o add mul i-
da abase p ojec s ha hey we e awa e o (and ha
we e no iden ified in he au oma ic and websi e
sea ches). The i les and abs ac s we e sc eened o
de e mine which a icles we e eligible o ull- ex
sc eening.
Two au ho s (IE and MB) e iewed he ull- ex o
all po en ially ele an s udies o de e mine final
inclusion.
Da a ex ac ion p ocess
A da a ex ac ion o m was designed o ex ac ele-
an da a om he selec ed s udies. Da a ex ac ion
was fi s pe o med by one e iewe (MB) wi h subse-
quen quali y assu ance pe o med by he second e-
iewe (IE). Disag eemen s we e esol ed h ough
discussion wi h a hi d e iewe (MA).
Analysis o s udy cha ac e is ics
We e ie ed in o ma ion abou he objec i e o he
s udies, he exposu e, he ou come, he s udy design,
and he numbe o di e en da abases and coun ies.
Fu he , we classified s udies acco ding o he me hods
ha we e used o indi idual-le el analyses and me a-
analyses. Rega ding he me a-analyses, we defined
h ee di e en le els o combining da a:
(1) An agg ega e le el app oach, in which sepa a e
analyses a e pe o med on da ase s om each
da abase and o e all esul s (adjus ed e ec
es ima es wi h confidence in e als) a e collec ed
o me a-analysis. The analyses a e usually
‘da abase-op imized’in he sense ha he bes
a ailable da a o each da abase a e being used.
This app oach allows using he no mal s a is ical
echniques o me a-analysis, including andom-
e ec s models, o accoun o he e ogenei y o
s udy esul s. Fu he , me a- eg ession can be used
o assessing a ia ion in e ec s ela ed o co a i-
a es, which may explain some o he o e all
he e ogenei y.
(2) A semi-agg ega e le el app oach, in which s a i-
fied da ase s wi h e en coun s (and o coho
s udies pe son ime) a e collec ed om all da a-
bases o one common analysis (e.g. a dis ibu ed
da a ne wo k). Da ase s can be s a ified on ou -
come, exposu e, and co a ia e pa e ns (age, sex,
ime since ini ia ion, and selec ed con ounde s).
Fo a coho s udy, his app oach employs a
Poisson eg ession model on ables o e en num-
be s and pe son ime s a ified by exposu e and
co a ia e pa e ns. Fo a case–con ol s udy, a lo-
gis ic eg ession model can simila ly be used o
analyze equency ables o cases and con ols
s a ified by di e en co a ia es.
(3) An indi idual le el app oach, in which indi idual
pa ien da a a e collec ed om all da abases o
one common analysis. In his scena io, he in o -
ma ion om di e en da abases has o be made
compa ible wi h ega d o defini ions o expo-
su es, ou comes, co a ia es, and ime windows.
He e ogenei y o s udy popula ions and a ia ion
in he e ec s bo h o exposu e and co a ia es be-
ween da abases may a ec he esul s. This may
be accoun ed o using s a is ical echniques
co ec ing o o e all a ia ion wi hin and be-
ween da abases.
Wi h ega d o da a managemen , we we e in e es ed
in which da a we e collec ed cen ally and whe he
cen al p og amming o he use o dis ibu ed common
p og ams was men ioned in he a icle. Mo eo e ,
mo i a ions o conduc ing he s udy (as s a ed in
he a icle) we e classified. Fo all ques ions he e
was a ca ego y ‘no specified’ ha could be icked.
This ca ego y is only shown in he esul ables i he e
was a leas one s udy wi h missing da a. F equen-
cies we e calcula ed o desc ibe he s udy cha ac e -
is ics, da a analysis echniques, da a managemen ,
and mo i a ions.
RESULTS
The PubMed and Embase sea ches iden ified 3083
publica ions (see Figu e 1). A e he sc eening o i-
les and abs ac s, 44 a icles we e selec ed o a ull-
ex sc eening. The manual sea ch iden ified an addi-
ional 176 publica ions; 22 om OMOP, 64 om
Mini-Sen inel, 34 om he HMO Resea ch Ne wo k
(based on a Pubmed sea ch, because no a icles we e
ound on he p ojec ’s websi e), 36 om EU-ADR,
11 om IMI-PROTECT, 2 om AsPEN, 2 om
CNODES, and 5 om indi idual p ojec s (da a no
shown in he flowcha ). A e e iew o i les and ab-
s ac s we selec ed 31 a icles o a ull- ex sc eening.
Figu e 1 shows ha om he 75 a icles selec ed o
ull- ex sc eening, 22 we e finally selec ed o
inclusion.
mul i-da abase s udies: a sys ema ic li e a u e e iew 899
© 2015 The Au ho s. Pha macoepidemiology and D ug Sa e y
published by John Wiley & Sons, L d.
Pha macoepidemiology and D ug Sa e y, 2015; 24: 897–905
DOI: 10.1002/pds
E- able 3 gi es an o e iew o he 22 s udies in-
cluded in ou e iew.
9–30
Six s udies we e published
be ween 2007 and 2010, while a majo i y o 16 s udies
was published be ween 2011 and 2013. Fo se en
s udies, he e was a me hod objec i e in addi ion o
an o e all (mos ly clinical) objec i e.
10,13,15,17,18,23,27
Figu e 2 shows which coun ies con ibu ed o he
mul i-da abase p ojec s. F om he 22 s udies, he e
we e 14 (64%) ha used a leas one da abase om
he U.S. o Canada. Hal o he s udies (50%) used a
leas one Eu opean da abase. Wi hin Eu ope, da a
om G ea B i ain we e mos o en used: he e we e
nine s udies (41%) ha used a B i ish da abase (wi h
he Clinical P ac ice Resea ch Da alink (CPRD) being
he mos equen ly used one, i.e. fi e imes). Fu he ,
he e we e fi e s udies ha used a leas one
Scandina ian da abase (23%), fi e s udies ha used a
da abase om he Ne he lands (23%), and fi e s udies
ha used an I alian da abase (23%).
Table 1 shows ha mos s udies add essed sa e y
(82%) a he han e ec i eness issues (23%). The de-
sign ha was mos o en used was he coho s udy de-
sign (82%) as opposed o he case–con ol design
(18%). The numbe o da abases used pe s udy anged
om 2 o 17 (median = 4.0), while he numbe o coun-
ies in ol ed anged om 1 o 6 (median = 2.5). The
ype o exposu e ha was mos equen ly s udied
was medica ion ela ed o he ne ous sys em (41%),
o example an idep essan s and dopamine agonis s.
In e ms o ou comes, ca diac diso de s we e mos e-
quen ly ep esen ed (36%), ollowed by all-cause mo -
ali y (23%) and ne ous sys em diso de s (18%). The
Figu e 1. Flowcha o he selec ion o a icles. * No pape s we e excluded because hey we e non-English ( he e we e 122 non-English pape s bu hey we e
excluded because o o he exclusion c i e ia)
m. . bazelie
e al.
900
© 2015 The Au ho s. Pha macoepidemiology and D ug Sa e y
published by John Wiley & Sons, L d.
Pha macoepidemiology and D ug Sa e y, 2015; 24: 897–905
DOI: 10.1002/pds
code sys em used o iden i y exposu e was o en no
specified (82%), while o he ou come his was less
o en he case (18%).
Table 2 shows ha logis ic eg ession was mos e-
quen ly used o indi idual-le el analyses (41%),
ollowed by Cox eg ession (23%) and Poisson eg es-
sion (14%). As me a-analysis me hod, a majo i y o
he s udies used an indi idual le el app oach (73%)
(see e- able 4 o he exac ca ego iza ion). The e we e
h ee s udies wi h a semi-agg ega e app oach (14%),
and six s udies pe o med an agg ega e me a-analysis
(27%). Fo wo s udies, he agg ega e me a-analysis
was he only me a-analysis ha was conduc ed (be-
cause da a we e collec ed on an agg ega e le el). The
o he ou agg ega e me a-analyses we e conduc ed in
addi ion o an indi idual pa ien da a me a-analysis ( h ee
s udies) o a semi-agg ega e me a-analysis (one s udy).
The e we e ou s udies ha collec ed semi-agg ega e
da ase s (18%), bu one o hem did no use his
in o ma ion in a me a-analysis ( eflec edin heca ego y
‘me a-analysis: none’). A quan i a i e he e ogenei y as-
sessmen was conduc ed in almos hal o he s udies
(45%) wi hou one specific es being mos popula .
Fo 12 s udies, cen al p og amming was men ioned
in he publica ion. The use o dis ibu ed common
p og ams was men ioned o fi e s udies; in h ee
cases hese common p og ams we e used in a semi-
agg ega e le el app oach, and he o he wo cases we e
ela ed o an agg ega e le el app oach.
A majo i y o he a icles mo i a ed hei mul i-da abase
s udy by powe o men ioned powe as a s eng h o hei
s udy (86%) (da a no shown in a able). Only one a icle
explici ly men ioned a e exposu e as an a gumen , and
h ee a icles made men ion o a a e ou come. Ex e nal
alidi y was s essed in six publica ions (27%), while only
h ee a icles men ioned compa ing di e en popula ions
o da abases as an a gumen o pe o m a mul i-da abase
p ojec (14%).
Figu e 2. Map o coun ies in ol ed in mul i-da abase s udies. Legend: - he numbe s eflec how many imes he coun y (a leas one da abase) was in-
ol ed in a mul i-da abase s udy ( he da ke he colo , he highe he numbe o s udies) - s ipes: coun y no in ol ed in any mul i-da abase s udy
mul i-da abase s udies: a sys ema ic li e a u e e iew 901
© 2015 The Au ho s. Pha macoepidemiology and D ug Sa e y
published by John Wiley & Sons, L d.
Pha macoepidemiology and D ug Sa e y, 2015; 24: 897–905
DOI: 10.1002/pds

DISCUSSION
Ou sys ema ic li e a u e sea ch iden ified 22
pha macoepidemiological mul i-da abase s udies, in
which da a we e combined o a p e-planned common
analysis o quan i a i e syn hesis. Fo indi idual-le el
analyses, logis ic eg ession was mos equen ly used,
ollowed by Cox and Poisson eg ession. Fo me a-
analyses, 16 s udies combined indi idual pa ien da a,
while a semi-agg ega e le el analysis was conduc ed
in h ee s udies and an agg ega e le el analysis in six.
I was a challenge o cap u e mul i-da abase obse -
a ional s udies in a sys ema ic li e a u e sea ch. Usu-
ally, he clinical opic was well ep esen ed in sea ch
e ms o keywo ds, bu he use o mo e han one inde-
penden da abase was much ha de o cap u e. The e is
a Mesh e m called ‘Mul icen e s udy’, bu his was
on he one hand oo b oad (e.g. also in ol ing s udies
ha selec ed hei pa ien s om wo di e en hospi als,
which was no he defini ion o mul i-da abase s udy
we we e looking o ) and on he o he hand missing
ou on ele an a icles. Among s udies ha used mo e
han one da abase, i was almos impossible o dis in-
guish s udies wi h pooled es ima es om s udies ha
only showed esul s om he sepa a e da abases, using
sea ch e ms. Because o hese issues, we we e qui e
libe al in defining he sea ch s a egy and manually
sc eened o e 3000 a icles, which only esul ed in
44 a icles ha we e selec ed o a ull- ex sc eening.
S ill, we missed ou on 31 a icles ha we e ound in
he addi ional manual sea ch.
Among he s udies finally selec ed o inclusion, he
ange o di e en exposu es and ou comes was qui e
b oad. This indica es ha he upcoming end o
pe o ming mul i-da abase obse a ional s udies s e ches
ou o e he en i e field o pha macoepidemiology.
App oxima ely hal o ou selec ed s udies used a
leas one da abase om he U.S. o Canada, and his
pe cen age was simila o Eu opean da abases. This
indica es ha No he n Ame ica and Eu ope cu en ly
ake an almos equal pa in con ibu ing o his ela-
i ely new field o mul i-da abase esea ch.
Rega ding he me hods o pe o ming such a s udy,
we ound ha he combina ion o indi idual pa ien
da a was he mos equen ly used echnique. I should
howe e be no ed ha one o ou inclusion c i e ia was
ha da a we e combined o a p e-planned common
analysis. The eby we excluded all ‘s anda d’me a-
analyses ha pool es ima es om di e en s udies o-
ge he on a pos -hoc basis, i.e. he app oach o com-
bining esul s om published li e a u e. This la e
ype o me a-analysis is equen ly used in he field
o clinical ials and is p obably also qui e common
Table 1. Objec i e, design, exposu e, and ou come
Numbe o s udies
( o al: n = 22) %
Objec i e ca ego y
E idence gene a ion 20 91%
Me hod / easibili y s udy 15%
Dual pu pose (combina ion o he abo e)15%
S udy ype (a)
Sa e y 18 82%
E ec i eness 5 23%
Design ca ego y
Coho s udy 18 82%
Case–con ol s udy 4 18%
Numbe o da abases
Range [2,17]
Mean 5.9
Median 4.0
Numbe o coun ies
Range [1,6]
Mean 2.4
Median 2.5
D ug exposu e: ATC ca ego y
N—Ne ous sys em 9 41%
A—Alimen a y ac and me abolism 4 18%
C—Ca dio ascula sys em 3 14%
M—Musculo-skele al sys em 3 14%
B—Blood and blood o ming o gans 15%
R—Respi a o y sys em 15%
S—Senso y o gans 15%
Ou come: All-cause mo ali y/MedDRA SOC (a)
Ca diac diso de s 8 36%
All-cause mo ali y 5 23%
Ne ous sys em diso de s 4 18%
Congeni al, amilial and gene ic diso de s 3 14%
Gas oin es inal diso de s 29%
Musculoskele al and connec i e issue
diso de s
29%
Blood and lympha ic sys em diso de s 15%
Eye diso de s 15%
In ec ions and in es a ions 15%
P egnancy,pue pe ium,and pe ina al
condi ions
15%
Renal and u ina y diso de s 15%
Respi a o y, ho acic and medias inal
diso de s
15%
Skin and subcu aneous issue diso de s 15%
D ug code sys ems (a)
ATC 4 18%
BNF 29%
No specified 18 82%
Ou come code sys ems (a)
ICD-9 13 59%
ICD-10 8 36%
ICPC 29%
RCD 29%
CCP 15%
CPT 15%
mRS 15%
No specified 4 18%
(a) One s udy could con ibu e o mo e han one ca ego y.
Abb e ia ions: ATC, Ana omical The apeu ic Chemical; BNF, B i ish Na-
ional Fo mula y; CCP, Canadian Classifica ion o Diagnos ic, The apeu ic
and Su gical P ocedu es; CPT, Cu en P ocedu al Te minology; ICD-9,
In e na ional Classifica ion o Diseases—9 h e ision; ICD-10, In e na-
ional Classifica ion o Diseases—10 h e ision; ICPC, In e na ional Clas-
sifica ion o P ima y Ca e; mRS, modified Rankin Scale; RCD, READ
CODE Classifica ion; SOC, sys em o gan class.
m. . bazelie
e al.
902
© 2015 The Au ho s. Pha macoepidemiology and D ug Sa e y
published by John Wiley & Sons, L d.
Pha macoepidemiology and D ug Sa e y, 2015; 24: 897–905
DOI: 10.1002/pds
in he field o obse a ional s udies, as i can be done
ela i ely quickly wi hou he need o ge ing access
o pa ien -le el heal hca e da a. I his ype o me a-
analysis would ha e been included in ou e iew, he
p opo ion o agg ega e me a-analyses would he e o e
ha e been much highe .
The e we e h ee s udies ha compa ed an indi id-
ual le el me a-analysis o an agg ega e le el (fixed o
andom e ec ) me a-analysis, using he same
da a.
10,13,18
In all h ee cases, he esul s we e simila
be ween he wo app oaches. Impo an ly, hese
agg ega e le el analyses we e designed wi h a p e-
specified common analysis plan, i.e. he same plan as
was used o he indi idual le el analyses, bu now
wi hou combining he indi idual pa ien da a bu
pooling da abase-specific es ima es oge he . F om a
logis ic poin o iew, his ype o agg ega e me a-
analysis could be an in e es ing al e na i e o an indi-
idual le el app oach, as no indi idual pa ien da a
ha e o be ans e ed. O he me hods ha do no e-
qui e sha ing o indi idual pa ien da a in ol e a dis-
ibu ed ne wo k app oach such as he EU-ADR
15
o
a case-cen e ed logis ic eg ession app oach as de-
sc ibed by Toh and cowo ke s.
27,31
I was no always clea ly s a ed in he a icles how
he da a we e combined. Especially he echnique o
combining indi idual pa ien da a (ins ead o combin-
ing semi-agg ega e o agg ega e da a) was no always
explici ly men ioned. Mos o he a icles clea ly had
a clinical ocus, and desc ip ions o da a managemen
we e o en e y sho o comple ely missing. Cen al
p og amming was men ioned o 12 s udies, bu he
ac ual numbe o s udies ha did so is p obably highe ,
because his echnique is e y likely o he s udies
ha combined indi idual pa ien da a (16 in o al).
Howe e , he use o dis ibu ed common p og ams
was equen ly men ioned o semi-agg ega e and ag-
g ega e le el app oaches. This is a good p ac ice, be-
cause di e en ways o s a is ical p og amming may
lead o he e ogenei y be ween esul s om di e en
da abases. In he indi idual le el app oach, i was o -
en no clea ly desc ibed i and how defini ions we e
kep simila be ween da a om di e en sou ces.
Powe was he mos s a ed eason o pe o ming a
mul i-da abase s udy. Compa ing di e en popula ions
o da abases was seldom men ioned. Many pape s, es-
pecially he indi idual pa ien da a s udies, did no
show any cha ac e is ics o pa ien s om he sepa a e
da abases. O e all, only hal o he s udies pe o med
a quan i a i e he e ogenei y assessmen .
The e a e impo an s eng hs and limi a ions o his
e iew. To ou knowledge, we we e he fi s o pe -
o m a sys ema ic li e a u e sea ch abou me hods used
in mul i-da abase s udies. Full- ex sc eening was pe -
o med by wo independen e iewe s, and da a ex ac-
ion was quali y checked by a second e iewe as well.
E en hough we pe o med a sys ema ic li e a u e
sea ch, we p obably missed ele an a icles, because
he o mula ion o a sui able sea ch s a egy was no
s aigh o wa d. Ou sea ches we e limi ed om
2007 onwa ds; howe e , in ou pilo sea ches wi h
no da e fil e applied we we e no able o iden i y
any s udies published p io o 2007 ha would po en-
ially fi ou inclusion and exclusion c i e ia.
Table 2. Da a analysis echniques and da a managemen
Numbe o s udies
( o al: n = 22) %
Indi idual-le el analyses
Logis ic eg ession 9 41%
Cox p opo ional haza ds model 5 23%
Poisson eg ession 3 14%
Incidence a e /incidence a e a io 29%
P e alence /p e alence a io 15%
Rela i e isk 15%
Gene alized linea model eg ession 15%
Exposu e– ime ela ion
Time-dependen exposu e 14 64%
In en ion o ea (e e /ne e ) 7 32%
Cumula i e exposu e (dose o ime)15%
Con ounde con ol
Con en ional 11 50%
P opensi y sco e 7 32%
Disease isk sco e 15%
None 3 14%
Me a-analysis me hod (a)
Indi idual 16 73%
Semi-agg ega e 3 14%
Agg ega e 6 27%
Fixed e ec 4 18%
Fixed e ec / andom e ec 29%
None 15%
He e ogenei y assessmen
Quan i a i e es 10 45%
I-squa ed 29%
Chi-squa ed 15%
Coch an’s Q s a is ic 15%
In e ac ion by da a sou ce 15%
Kaplan–Meie s a ified by da abase 15%
No specified 4 18%
Quali a i e s a emen s only 15%
No specified 11 50%
P og amming
Cen al (leading cen e ) 12 55%
Decen al 00%
No specified 10 45%
Da a collec ed cen ally
Indi idual-based egis e da a 16 73%
Semi-agg ega e da ase s 4 18%
Agg ega e esul s 29%
Dis ibu ed common p og ams
Yes 5 23%
No specified 17 77%
(a) One s udy could con ibu e o mo e han one ca ego y.
mul i-da abase s udies: a sys ema ic li e a u e e iew 903
© 2015 The Au ho s. Pha macoepidemiology and D ug Sa e y
published by John Wiley & Sons, L d.
Pha macoepidemiology and D ug Sa e y, 2015; 24: 897–905
DOI: 10.1002/pds
Classifica ion in o he di e en le els o da a combin-
ing was done o he e iewe s’bes e o , bu was
some imes based on e y li le in o ma ion. Classifica-
ion o mo i a ions o pe o m he s udy may ha e
been suscep ible o subjec i e in e p e a ion.
In conclusion, mul i-da abase s udies a e becoming
mo e popula in obse a ional esea ch. We eel ha
he e is oom o imp o emen in making clea o he
eade how da a om di e en da abases we e com-
bined; on an indi idual, semi-agg ega e, o agg ega e
le el. Fo all scena ios, i is use ul o know how defi-
ni ions o exposu es, ou comes, con ounde s, and
ime-windows we e kep consis en ac oss he da a-
bases. Fu he , i should be explained how da a man-
agemen was o ganized, which da a we e collec ed
cen ally and whe he cen al p og amming o dis ib-
u ed common p og ams we e used. I is use ul o show
cha ac e is ics o pa ien s om he sepa a e da abases
o enable he eade o e alua e whe he he e we e
impo an di e ences. When combining da a om
di e en da abases, he pe o mance o he e ogenei y
assessmen s should become common p ac ice. E en
i he objec i e o a s udy is clinical a he han me h-
odological, all his in o ma ion enables a be e in e -
p e a ion o he esul s o a mul i-da abase s udy.
CONFLICT OF INTEREST
Ma loes T. Bazelie ’s employmen a U ech Uni e -
si y is unded by he CARING p ojec (Eu opean
Communi y’s Se en h F amewo k P og am g an
ag eemen numbe 282526).
F ank de V ies is employed by U ech Uni e si y as
a senio esea che , conduc ing esea ch coo dina ed
by The Cen e o Resea ch Me hods. The Cen e o
Resea ch Me hods has ecei ed un es ic ed unding
om he Ne he lands O ganiza ion o Heal h Re-
sea ch and De elopmen (ZonMW), he Du ch Heal h
Ca e Insu ance Boa d (CVZ), he Royal Du ch Pha -
macis s Associa ion (KNMP), he p i a e–public
unded Top Ins i u e Pha ma (www. ipha ma.nl, in-
cludes co- unding om uni e si ies, go e nmen , and
indus y), he EU Inno a i e Medicines Ini ia i e
(IMI), he EU 7 h F amewo k P og am (FP7), and
he Du ch Minis y o Heal h and indus y (including
GlaxoSmi hKline, Pfize , and o he s).
Ma ie L. De B uin is employed by U ech Uni e -
si y as a senio esea che conduc ing esea ch in col-
labo a ion wi h he WHO Collabo a ing Cen e o
pha maceu ical policy and egula ion. This Cen e e-
cei es no di ec unding o dona ions om p i a e
pa ies, including pha ma indus y. Resea ch unding
om public–p i a e pa ne ships, e.g. IMI, TI Pha ma
(www. ipha ma.nl) is accep ed unde he condi ion
ha no company-specific p oduc o company ela ed
s udy is conduc ed. The Cen e has ecei ed un e-
s ic ed esea ch unding om public sou ces, e.g.
Ne he lands O ganiza ion o Heal h Resea ch and De-
elopmen (ZonMW), he Du ch Heal h Ca e Insu -
ance Boa d (CVZ), EU 7 h F amewo k P og am
(FP7), Du ch Medicines E alua ion Boa d (MEB),
and Du ch Minis y o Heal h.
Mo en Ande sen pa icipa es/has pa icipa ed in e-
sea ch p ojec s unded by As aZeneca, Lundbeck,
Me ck Sha p & Dohme, No a is, Nycomed, and
Pfize wi h g an s ecei ed by he ins i u ions whe e
he has been employed. He has pe sonally ecei ed ees
o leading and eaching pha macoepidemiology
cou ses a anged by Medicademy, he Danish Associ-
a ion o he Pha maceu ical Indus y.
KEY POINTS
•The upcoming end o pe o ming mul i-
da abase obse a ional s udies s e ches ou o e
he en i e field o pha macoepidemiology.
•Rega ding he me hods o pe o ming such a s udy,
we ound ha he combina ion o indi idual pa ien
da a was he mos equen ly used echnique.
•The e is oom o imp o emen in making clea o
eade s how da a om di e en da abases we e
combined (on an indi idual le el o agg ega e
le el), how da a managemen was o ganized, and
whe he cen al p og amming was used.
•I is use ul o show cha ac e is ics o pa ien s
om he sepa a e da abases and he pe o mance
o he e ogenei y assessmen s should become
common p ac ice.
ETHICS STATEMENT
The au ho s confi m o ha e adhe ed o E hics p inci-
ples du ing all phases o he s udy.
ACKNOWLEDGEMENTS
The esea ch leading o he esul s o his s udy has
ecei ed unding om he Eu opean Communi y’s
Se en h F amewo k P og amme (FP-7) unde g an
ag eemen numbe 282526, he CARING p ojec .
The unding sou ce had no ole in s udy design, da a
collec ion, da a analysis, da a in e p e a ion, o w i ing
o he epo .
m. . bazelie
e al.
904
© 2015 The Au ho s. Pha macoepidemiology and D ug Sa e y
published by John Wiley & Sons, L d.
Pha macoepidemiology and D ug Sa e y, 2015; 24: 897–905
DOI: 10.1002/pds
REFERENCES
1. The obse a ional medical ou comes pa ne ship. 2009; A ailable a : h p://
www.omop. nih.o g [14 Ap il 2015].
2. The mini-sen inel p og am. 2010; A ailable a : h p://www.mini-sen inel.o g [14
Ap il 2015].
3. The HMO esea ch ne wo k. 2013; A ailable a : h p://www.hmo esea ch-
ne wo k.o g [14 Ap il 2015].
4. Suissa S, Hen y D, Cae ano P, e al. Canadian Ne wo k o Obse a ional D ug
E ec S udies (CNODES). CNODES: he Canadian Ne wo k o Obse a ional
D ug E ec S udies. Open Med 2012; 6(4): e134–e140.
5. The Canadian Ne wo k o Obse a ional D ug E ec S udies. 2013; A ailable
a : h p://www.cnodes.ca [14 Ap il 2015].
6. The EU-ADR p ojec . (2008) A ailable a : h p://euad -p ojec .o g [14 Ap il
2015].
7. The Pha macoepidemiological Resea ch on Ou comes o The apeu ics by a
Eu opean Conso ium (PROTECT). 2009; A ailable a : h p://www.imi-p o-
ec .eu [14 Ap il 2015].
8. AsPEN collabo a o s, Ande sen M, Be gman U, e al. The Asian
Pha macoepidemiology Ne wo k (AsPEN): p omo ing mul i-na ional collabo a-
ion o pha macoepidemiologic esea ch in Asia. Pha macoepidemiol D ug
Sa 2013; 22(7): 700–704.
9. T ifi ò G, Mokhles MM, Dieleman JP, e al. Risk o ca diac al e egu gi a ion
wi h dopamine agonis use in Pa kinson’s disease and hype p olac inaemia: a
mul i-coun y, nes ed case–con ol s udy. D ug Sa 2012; 35(2): 159–171.
10. Mokhles MM, T ifi ò G, Dieleman JP, e al. The isk o new onse hea ailu e
associa ed wi h dopamine agonis use in Pa kinson’s disease. Pha macol Res
2012; 65(3): 358–364.
11. Kiele H, A ama M, Engeland A, e al. Selec i e se o onin eup ake inhibi o s du ing
p egnancy and isk o pe sis en pulmona y hype ension in he newbo n: popula ion
based coho s udy om he fi e No dic coun ies. BMJ 2012; 344: d8012.
12. S ephansson O, Kiele H, Haglund B, e al. Selec i e se o onin eup ake inhibi-
o s du ing p egnancy and isk o s illbi h and in an mo ali y. JAMA 2013;
309(1): 48–54.
13. Bazelie MT, de V ies F, Ves e gaa d P, e al. Risk o ac u e wi h
hiazolidinediones: an indi idual pa ien da a me a-analysis. F on Endoc inol
(Lausanne) 2013; 4(11): 1–9.
14. And ade SE, McPhillips H, Lo en D, e al. An idep essan medica ion use and
isk o pe sis en pulmona y hype ension o he newbo n. Pha macoepidemiol
D ug Sa 2009; 18(3): 246–252.
15. Coloma PM, Schuemie MJ, T ifi ò G, e al. Combining elec onic heal hca e da-
abases in Eu ope o allow o la ge-scale d ug sa e y moni o ing: he EU-ADR
P ojec . Pha macoepidemiol D ug Sa 2011; 20(1): 1–11.
16. Da is RL, Rubanowice D, McPhillips H, e al. Resea ch in The apeu ics. Risks
o congeni al mal o ma ions and pe ina al e en s among in an s exposed o an i-
dep essan medica ions du ing p egnancy. Pha macoepidemiol D ug Sa 2007;
16(10): 1086–1094.
17. Do mu h CR, Hemmelga n BR, Pa e son JM, e al. Use o high po ency s a ins
and a es o admission o acu e kidney inju y: mul icen e , e ospec i e obse -
a ional analysis o adminis a i e da abases. BMJ 2013; 346: 880.
18. Engel e ST, Soinne L, Ringleb P, e al. IV h ombolysis and s a ins. Neu ology
2011; 77(9): 888–895.
19. Filion KB, Cha eau D, Ta gownik LE, e al. P o on pump inhibi o s and he isk
o hospi alisa ion o communi y-acqui ed pneumonia: eplica ed coho s udies
wi h me a-analysis. Gu 2014; 63(4): 552–558.
20. Habel LA, Coope WO, Sox CM, e al. ADHD medica ions and isk o se ious
ca dio ascula e en s in young and middle-aged adul s. JAMA 2011; 306(24):
2673–2683.
21. Hagiwa a M, Delea TE, S an o d RH, S empel DA. S epping down o flu icasone
p opiona e o a lowe dose o flu icasone p opiona e/salme e ol combina ion in
as hma pa ien s ecen ly ini ia ing combina ion he apy. Alle gy As hma P oc
2010; 31(3): 203–210.
22. Henk HJ, Tei elbaum A, Pe ez JR, Kau a S. Pe sis ency wi h zoled onic acid is
associa ed wi h clinical benefi in pa ien s wi h mul iple myeloma. Am J Hema ol
2012; 87(5): 490–495.
23. Rassen JA, Choudh y NK, A o n J, Schneeweiss S. Ca dio ascula ou comes
and mo ali y in pa ien s using clopidog el wi h p o on pump inhibi o s a e pe -
cu aneous co ona y in e en ion o acu e co ona y synd ome. Ci cula ion 2009;
120(23): 2322–2329.
24. Ray WA, Va as-Lo enzo C, Chung CP, e al. Ca dio ascula isks o nons e oi-
dal an iinflamma o y d ugs in pa ien s a e hospi aliza ion o se ious co ona y
hea disease. Ci c Ca dio asc Qual Ou comes 2009; 2(3): 155–163.
25. Schelleman H, Bilke WB, Kimmel SE, e al. Me hylphenida e and isk o
se ious ca dio ascula e en s in adul s. Am J Psychia y 2012; 169(2):
178–185.
26. Schwa z GF, Ko ak S, Ma dekian J, Fain JM. Incidence o new coding o d y
eye and ocula in ec ion in open-angle glaucoma and ocula hype ension pa-
ien s ea ed wi h p os aglandin analogs: e ospec i e analysis o h ee
medical/pha macy claims da abases. BMC Oph halmol 2011; 11: 14.
27. Toh S, Reichman ME, Hous oun M, e al. Compa a i e isk o angioedema as-
socia ed wi h he use o d ugs ha a ge he enin–angio ensin–aldos e one sys-
em. A ch In e n Med 2012; 172(20): 1582–1589.
28. Toh S, Bake MA, B own JS, Ko negay C, Pla R, Mini-Sen inel In es iga o s.
Rapid assessmen o ca dio ascula isk among use s o smoking cessa ion d ugs
wi hin he US Food and D ug Adminis a ion’s Mini-Sen inel p og am. JAMA
In e n Med 2013; 173(9): 817–819.
29. Tsai TT, Ho PM, Xu S, e al. Inc eased isk o bleeding in pa ien s on clopidog el
he apy a e d ug-elu ing s en s implan a ion: insigh s om he HMO Resea ch
Ne wo k-S en Regis y (HMORN-s en ). Ci c Ca dio asc In e 2010; 3(3):
230–235.
30. an Soes EM, Valkho VE, Mazzaglia G, e al. Subop imal gas op o ec i e
co e age o NSAID use and he isk o uppe gas oin es inal bleeding and ul-
ce s: an obse a ional s udy using h ee Eu opean da abases. Gu 2011; 60(12):
1650–1659.
31. Toh S, Reichman ME, Hous oun M, e al. Mul i a iable con ounding adjus men
in dis ibu ed da a ne wo ks wi hou sha ing o pa ien -le el da a.
Pha macoepidemiol D ug Sa 2013; 22(11): 1171–1177.
SUPPORTING INFORMATION
Addi ional suppo ing in o ma ion may be ound in
he online e sion o his a icle a he publishe ’s
web si e.
mul i-da abase s udies: a sys ema ic li e a u e e iew 905
© 2015 The Au ho s. Pha macoepidemiology and D ug Sa e y
published by John Wiley & Sons, L d.
Pha macoepidemiology and D ug Sa e y, 2015; 24: 897–905
DOI: 10.1002/pds