10.savarese meta analysis

8/18/2019 10.Savarese Meta Analysis

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META-ANALYSIS AND SYSTEMATICREVIEW

Gianluigi Savarese, MD, FESC, ACC FIT

Department of Advanced Biomedical Sciences, Federico II University, Naples,Italy

Department of Medicine, Solna, Karolinska Institutet, Stockholm, Seden


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!hat is a Systematic"evie#

$A revie that is conducted accordin%to clearly stated, scienti&c research

methods, and is desi%ned to minimi'e(iases and errors inherent totraditional, narrative revies)*

Kevin +) +hun%, MD, atricia B) Burns, M-, -) Myra Kim, ScD, $+linical erspective. A ractical /uide to Meta0Analysis)* 1he 2ournal of -and Sur%ery) 3ol) 45A No)56 Decem(er 7668) p)5895


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!hat is the si%ni&cance ofSystematic "evies#

• 1he lar%e amount of medical literature re:uires

clinicians and researchers alike to rely on systematic

revies in order to make an informed decision)

• Systematic "evies minimi'e (ias) $A systematic revie

is a more scienti&c method of summari'in% literature

(ecause speci&c protocols are used to determine hich

studies ill (e included in the revie)*

Mar%aliot, ;vi, Kevin +) +hun%) $Systematic "evies. A rimer for lastic Sur%ery "esearch)* "S 2ournal) 576 p)5?4@


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!hy are Systematic "eviesNecessary#

$1he volume of pu(lished material makes it impractical for an

individual clinician to remain up to date on a variety of

common conditions) 1his is further complicated hen

individual studies report conictin% conclusions, a pro(lem

that is prevalent hen small patient samples and

retrospective desi%ns are used)*



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+haracteristics of Systematic"evies

• 1o possi(le approaches.

– or :ualitative synthesis

– statistical synthesis of data =meta0analysis> if appropriate and possi(le


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-ypothesis

A systematic revie should (e (ased

on principles of hypothesis testin%, andthe hypotheses must (e conceived a

priori)


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• Identify your studies

• Determine eli%i(ility of studies

apriori to avoid (ias – Inclusion. hich ones to keep

–Cclusion. hich ones to thro out

• A(stract Data from the studies• Analy'e data in the studies

statistically

Four steps


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iterature Search

A comprehensive and reproduci(leliterature search is the foundation of a

systematic revie)


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iterature Search G "isk ofBias

• Englis"-language #ias 0 occurs hen revieerseCclude papers pu(lished in lan%ua%es other than n%lish

• Ci!a!ion #ias 0 occurs hen studies ith si%ni&cant orpositive results are referenced in other pu(lications,

compared ith studies ith inconclusive or ne%ative

&ndin%s

• $u#li%a!ion &ias 0 selective pu(lication of articlesthat sho positive treatment of eHects and statistical

si%ni&cance)


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Data +ollection

• 1he list of data to (e eCtracted should (e decideda priori'

• A data eCtraction form should (e used so that thesame data are eCtracted from each study andmissin% data are clearly apparent)

• 1o (e sure that data eCtraction is accurate andreproduci(le, it should (e performed (y at leastto independent readers)

• Disa%reement (eteen readers could (e solved (ya%reements or (y a third revieer



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Data +ollection

+ollected data includes. – S!u() %"ara%!eris!i%s =year and ournal of

pu(lication, num(er of patients in each arm,treatments performed, duration of follo0up>

– Sa*ple (e*ograp"i%s =a%e, J males orfemales>

–Sa*ple %"ara%!eris!i%s =traditional +3 riskfactors 0 J hypertensive pts, J dia(etic pts, Jdyslipidemic pts, J smokers G concomitanttreatments, comor(idities, etc>

–+u!%o*e (a!a =all0cause death, +3 death, MI,stroke, etc>


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/"AD

/radin% of

"ecommendationsAssessment, Developmentand valuation

/uyatt /-, ECman AD, Kun' ", 3ist /, Falck0Ltter L, Schnemann -2 /"AD !orkin% /roup) !hat is O:uality of evidenceO andhy is it important to clinicians# BM2) 766? May 4448=98P5>.@@P0?)


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/uyatt /-, ECman AD, Kun' ", 3ist /, Falck0Ltter L, Schnemann -2 /"AD !orkin% /roup) !hat is O:uality of evidenceO andhy is it important to clinicians# BM2) 766? May 4448=98P5>.@@P0?)


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Data Synthesis

Data could (e summari'ed:uantitatively if study desi%ns are nottoo diHerent in.

•outcome de&nition =compositeoutcome#>

•population si'es

•population characteristics

•interventions-1"E/NI1L


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Data Synthesis

Ence the data have (een eCtractedand their :uality and validity assessed,

the outcomes of individual studiesithin a systematic revie may (epooled and presented as summaryoutcome or eHect

META-ANALYSIS


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!hat is meta analysis#

Quantitative approach for systematically

combining results of previous research toarrive at conclusions about the body ofresearch.


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!hat does it mean#

• uan!i!a!ive nu*#ers

• S)s!e*a!i% *e!"o(i%al

• %o*#ining pu!!ing !oge!"er

• previous resear%" ."a!/s

alrea() (one• %on%lusions ne. 0no.le(ge


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Meta0analysis. StatisticalModels

• 1here are 7 statistical models used in ameta0analysis. – FiCed eHects.

5)Hect of treatment is the same for every study7)o hetero%eneity

– "andom eHects.

5)1rue eHect estimate for each study varies7)-i%h hetero%eneity

4)rovide lar%er +I


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-etero%eneity

• Clini%al "e!erogenei!) varia(ility in theparticipants, interventions and outcomes studied

1• Me!"o(ologi%al "e!erogenei!) varia(ility in

study desi%n

• S!a!is!i%al "e!erogenei!) 3aria(ility in the

intervention eHects (ein% evaluated in thediHerent studies) It is a conse:uence of clinical ormethodolo%ical diversity, or (oth, amon% thestudies)

-i%%ins 21, /reen S =editors>) +ochrane -and(ook for Systematic "evies of Interventions 3ersion P)5)6 Qupdated March

7655R) 1he +ochrane +olla(oration, 7655) Availa(le from )cochrane0hand(ook)or%)


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-etero%eneity assessment

• If con&dence intervals for the results of individual studies=%enerally depicted %raphically usin% hori'ontal lines> have pooroverlap, this %enerally indicates the presence of statisticalhetero%eneity)

• +ochrane statistic. It is calculated as the ei%hted sum ofs:uared diHerences (eteen individual study eHects and thepooled eHect across studies, ith the ei%hts (ein% those usedin the poolin% method) A p value decided apriori de&nes thepresence of si%ni&cant hetero%eneity)

• I7 statistic. It descri(es the percenta%e of variation across studies

that is due to hetero%eneity rather than chance) 6J to T6J. hetero%eneity mi%ht not (e important 46J to 86J. may represent moderate hetero%eneity P6J to @6J. may represent su(stantial hetero%eneity 9PJ to 566J. considera(le hetero%eneity)

-i%%ins 21, /reen S =editors>) +ochrane -and(ook for Systematic "evies of Interventions 3ersion P)5)6 Qupdated March



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Strate%ies for addressin%hetero%eneity

• +heck a%ain that the data are correct• Do not do a meta0analysis• Cplore hetero%eneity =su(%roup analysis,

meta0re%ression>• I%nore hetero%eneity =there is no an

intervention eHect (ut a distri(ution ofintervention eHects>

• erform a random0eHects meta0analysis

=hen hetero%eneity cannot (e eCplained>• +han%e the eHect measure =diHerent scalesin diHerent studies>

• Cclude studies =outlyin% studies>-i%%ins 21, /reen S =editors>) +ochrane -and(ook for Systematic "evies of Interventions 3ersion P)5)6 Qupdated March



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Sensitivity analysis

• Ene study removed meta0analysis

• Meta0re%ression analysis


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u(lication Bias

u(lication (ias arises hen trials ithstatistically si%ni&cant results are morelikely to (e pu(lished and cited, and

are preferentially pu(lished in n%lishlan%ua%e ournals and those indeCed inMedline

2ni , -olenstein F, Sterne 2, Bartlett +, %%er M) Direction and impact of lan%ua%e (ias in meta0analyses of controlled trials.empirical study) International 2ournal of pidemiolo%y 766545.55P0574)


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u(lication Bias

• A funnel plot is a simple scatter plot of theintervention eHect estimates =E", lo%E"> fromindividual studies a%ainst some measure of eachstudys si'e or precision =standard error,

5, Mantel0-aens'el ei%ht>)

• 1he (est choice of C aCis for detectin% the small

sample eHect is the lo% odds ratio) 1his is(ecause the scale is not constrained and(ecause the plot ill (e the same shape hetherthe outcome is de&ned as occurrence or non0occurrence of event)

Sterne 2A+, %%er M) Funnel plots for detectin% (ias in meta0analysis. /uidelines on choice of aCis) 2ournal of +linical

pidemiolo%y 7665PT.56T8056PP)


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Symmetrical plot in the a(sence of(ias =opencircles indicate smaller studiesshoin% no (ene&cial eHects>

Asymmetrical plot in the presence ofpu(lication (ias =smaller studies

shoin% no (ene&cial eHects aremissin%>

Asymmetrical plot in the presence of(ias due to lo methodolo%ical:uality of smaller studies =opencircles indicate small studies ofinade:uate :uality hose results are

(iased toards lar%er (ene&cialeHects

2onathan A et al) 1he Stata 2ournal766T T.579


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u(lication Bias

Ntot is the total sample si'e, N and N+ are the si'es of the eCperimentaland control intervention %roups, S is the total num(er of events across (oth%roups and F V Ntot G S) Note that only the &rst three of these tests =Be%%

5@@T, %%er 5@@9a, 1an% 7666> can (e used for continuous outcomes)


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rotocols

1he purpose of "ISMA =referred"eportin% Items for Systematic"evies and Meta0Analyses> %uidelines

is to provide proper procedures forconductin% a meta0analysis and tostandardi'e the methods of reportin% a

meta0analysis)


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Savarese / et al 2 Am +oll +ardiol765485.545


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• An%iotensin0convertin% en'yme inhi(itors =A+0Is>

are recommended for reduction of cardiovascular

=+3> events in patients at hi%h +3 risk ithout

heart failure =-F>)

• In contrast, +3 eHects of an%iotensin receptor(lockers =A"Bs> on maor clinical outcomes in

patients ithout -F are less certain as maorclinical trials comparin% A"Bs vs place(o reportedconictin% results)

Back%round



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Methods G Inclusion +riteria

• "eport of at least one clinical outcome =all0cause

death, +3 death, myocardial infarction, stroke,ne onset heart failure, ne onset dia(etesmellitus>)

• "andomi'ed, place(o0controlled trials usin% A+0Is or A"Bs as treatments)



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• Meta0analysis as performed to assess theinuence of treatments on outcomes)

• Statistical homo%eneity as assessed usin% statistic and further :uanti&ed ith the I7 statistic)

• Meta0re%ression as performed to test the

inuence of potential eHect modi&ers on results)

• u(lication (ias as assessed usin% linearre%ression test (y %%er and Macaskills modi&ed

test)

Methods G Statisticalmethods



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"esults G Search Strate%y



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"esults G opulationcharacteristics


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"esults G opulationcharacteristics


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A+0Is si%ni&cantly reduced

the risk of the compositeoutcome (y 5T)@Jcompared to place(o=pV6)665>)

A"Bs si%ni&cantly reducedthe risk of the compositeoutcome (y 9)6Jcompared to place(o=pV6)657>)

"esults G +ompositeEutcome



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56J reduction of +3

death did not achievestatistical si%ni&cancein A+0Is trials=pV6)6?9>)

A"Bs did not reducethe risk of +3 death

=pV6)98?>

"esults G +3 Death



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A+0Is si%ni&cantly

reduced the risk of MI (y59)9J =pW6)665>

@)PJ reduction of MI riskdid not achieve statistical

si%ni&cance in A"Bs trials=pV6)6?8>)

"esults G Myocardialinfarction



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A"Bs si%ni&cantlyreduced the risk ofstroke (y @)5J

=pV6)655>)

A+0Is si%ni&cantlyreduced the risk of

stroke (y 5@)8J=pV6)66T>

"esults G Stroke



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A+0Is reduced the risk of

all0cause death (y ?)4J=pV6)66?>)

No si%ni&cant eHect asfound on the risk of all0cause death in A"Bs trials

=pV6)?88>)

"esults G All +ause Death



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No si%ni&cant eHectas found on therisk of ne onset

-F in A"Bs trials=pV6)?88>)

A+0Is reduced therisk of ne onset

-F (y 76)PJ=pV6)665>)

"esults G Ne onset -F



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A+0Is reduced

the risk of neonset dia(etes(y 54)9J=pV6)657>

A"Bssi%ni&cantlyreduced therisk of neonset DM (y56)8J=pW6)65>)

"esults G Ne onset DM



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"esults G Su(%roup analysis



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"esults G Meta0re%ressionanalysis


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• In comparison to place(o, A+0Issu(stantially reduce the composite of +3death


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Fre:uentist approach

+lassical methods are, usually (ased on al%orithms usin%eCplicit formulas)

mainassumpti

onsof themodel

results ofstudies

=usually"+1s>

1ransformations of inputdata

Resul!s o2 Me!a-anal)sis


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B i M t A l i


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Bayesian Meta0AnalysisAssessin% clinical si%ni&cance

Resul!s o2 Me!a-anal)sis

M+M+simulations

non0informative

priordistri(utions

results ofstudies

Ans.ering !"e 6ues!ion 7o.pro#a#le is !"a! !"e resul! is

%lini%all) signi%an!8

ossi(le too(tain due toknoled%e of

holedistri(ution

esta(lishin% thelevel of clinical

si%ni&cant result=e)%) "" X 5)7>

mainassumptionsof the

model

5 Fre:uentist vs Bayesian


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Fre:uentist vs Bayesianapproach

Bayesian approachFre:uentialist

methods

philosophy

First. assumptions andconstruction

then. inputin% results of studies

+onstruction(ased on the

results of studies

eCi(ility YES N+

computation

Makov +hain Monte +arlosimulations

formulas

softare specialistic, e)%) !inBU/S no specialre:uirements

Netork Meta Analysis


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Netork Meta0Analysis=Multiple Treatments Meta-Analysis, Mixed Treatment Comparisons)

• Combine direct + indirect estimates of multiple treatment effects

• Internally consistent set of estimates that respects randomiation

• !stimate effect of each inter"ention relati"e to e"ery otherwhether or not there is direct comparison in studies

• Calculate probability that each treatment is most effecti"e

• Compared to con"entional pair-#ise meta-analysis$

• %reater precision in summary estimates

• &an'in( of treatments accordin( to effecti"eness


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Netork Meta Analysis


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paroCetine

sertraline

citalopram

uoCetine

uvoCamine

milnacipran

venlafaCine

re(oCetine

(upropion

mirta'apineduloCetine

escitalopram

sertraline

milnacipran

(upropion

paroCetine

milnacipran

duloCetine

escitalopram

uvoCamine

#

7 meta-analyses of pair#ise comparisons published

Netork Meta0Analysis=Multiple Treatments Meta-Analysis, Mixed Treatment Comparisons)


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!hat is an individual patients


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!hat is an individual patientsdata Meta0analysis#

• Involves the central collection, checkin%and analysis of updated individualpatient data

• Include all properly randomised trials,pu(lished and unpu(lished

• Include all patients in an intention0to0treat analysis

& f


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Bene&ts of ID

• +arry out time0to0event analyses

• Enly practical ay to do su(%roup analyses

• More eCi(le analysis of outcomes• +arry out detailed data checkin%

• nsure :uality of randomisation and follo up

• nsure appropriateness of analysis

• Update follo up information


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Ether Bene&ts

• More complete identi&cation of trials

• Better compliance in providin% missin% data• More (alanced interpretation of results

• !ider endorsement and dissemination of results

• Better clari&cation of further research

• +olla(oration on further research

THANKS FO TH! ATT!NT"ON###


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10.savarese meta analysis

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