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15 Meta-Analysis and Pooled Analysis 15 Meta-Analysisand PooledAnalysis - Geneticand EnvironmentalData CamilleRagin and EmanuelaTaioli Ilniversity of Pittsburgh Cancer Institute and School of Public Health, Pittsburgh, PA, USA 15.1.INTRODUCTION Four steps can be identified when performing a meta-analysis(See Box 15.1) A large amount of data have been produced markers measured and published on biological 1. Identificationofthe relevantstudies. a common obstacle in in human subjects, but 2. Setting of the eligibility criteria for the inclu- has been the lack reaching definite conclusions sion and exclusion in the meta-analvsisof the power the individual studies.To of statistical of identified studies. problem, it is customary to per- overcome this 3. Abstracting the relevant data. published studies, while form summariesof the 4. Analysis of the data, including formal statisti- Reviews of the new, larger studies are completed. cal testing for heterogeneity and investigation performed in two main ways: by evidence can be of the reasonsfor heterogeneityif it exists. completing a meta-analysisof publisheddata, or a pooled analysisof individual data (both published and unpublished). Databasesearching, eligibility criteria and data extraction A bibliographic search (e.g. in MEDLINE or 15.2. META.ANATYSIS EMBASE) should be conducted to identify the Meta-analysisprovides summary estimates by studiesof interest.Potentially relevant publications combining the individual results published by inde- may be identified from the abstracts,and full-text pendent scientists.This approachincreases power, versions should be obtained for a review. The producesa more accurateestimate of the risk while next step is to define eligibility criteria for the reducing the possibility of false-negative results meta-analysis, since not all studies can or should (Greenland 1987). Some limitations are the impos- be included in a meta-analysis. This is to ensure sibility of performing more refined analyses,such reproducibility of the meta-analysisand minimize as dose-response and stratified analyses. While bias. If the eligibility criteria are well defined, severalguidelines and methodological papershave any person should be able to reproduce the path been published for clinical trials, the organization followed for identifying studies to be included. and summarization of data for observational stud- Bias will be reduced by the systematic selection ies (Blettneret al.1999; Stroupet aI.20OO)and for of studies, which should not be influenced by the molecular genetic research(Bogardus et al. 1999) knowledge of the study results or aspects of the has been addressedless frequently. studv conduct. The basic considerationsin definine Molecular Epidgmiology of Chronic Drseases, Edited by C. P. Wild, P. Vineis, md S' Garte @ 2008 John Wiley & Sons, Ltd tssuEslN 200 META-ANATYSISAND POOTEDANATYSIS - CENETICAND ENVIRONMENTALDATA Summaryestirnafes and assessment Box 15.1 Four steps to performing a meta- of heterogeneity analysis The summary estimate provides the overall effect l. Identify the relevant studies. of the measured outcome by combining the data 2. Set the eligibility criteria for the inclusion from all the studies included in the meta-analysis. and exclusion. A weighted averageof the results of each study is 3. Abstract the relevant data. used to calculate this summary estimate;the simple 4. Analyse the data: arithmetic average would be misleading. The size (a) Generatesummary estimates. of the study must be taken into considerationwhen (b) Testing for heterogeneity. calculating the summary estimate. Larger studies (c) Assesspublication bias. have more weight than smaller studies because their results are less subject to chance. Fixed effects and random effects are two types of models eligibility criteria for a meta-analysis should used for calculating the summary estimate.Fixed include study design, years of publication, com- fficts models consider that the variability between pleteness of information in the publication, simi- studies is due to random variation becauseof the size of the study. This meansthat if all the studies larities of treatment and/or exposure, languages, Figure 15.1 F (i.e. and the choice of studies that have overlapping were large, they would yield the same results datasets. the studies are homogeneous).Statistical methods Data extraction should include data on the rel- which calculate the summary estimates based evant outcomes and the general characteristicsof on the assumption of fixed effects include the where a value each study such as samples size, source of the Mantel-Haenszel method (Mantel and Haenszel ogeneitYbetu control population, race or ethnicity of the study 1959),the Petomethod (Yusuf eral. 1985),general Afixedeff' population. variance-basedmethods (Wolf 1986) and the CI methods (Greenland 1987; Prentice and Thomas the summarY bet 1987). Random effects models consider that the observed shoul Graphical summaries variability between studies is due to distinct differ- model- acrossstudie The results for each of the studies included in the encesbetween the studies (i.e. the studies are het- differences t meta-analysis can be graphically displayed with erogeneous).Heterogeneity can arise when there the meta-ant the odds ratios (ODs) or relative risk ratios (RRs) are differences in study design, lengths of follow- differences. and confidence intervals (CIs), using a Forest up or inclusion criteria of the study participants. estimate do' plot (Figure 15.1).Each study is representedby a The statistical methods describedby DerSimonian sometimes c square and a solid line. The squarecorresponds to and Laird (1986) calculate the summary estimates mates or fitt the OR or RR. The size of each squarecorresponds basedon the assumptionof random effects. (due to het to the contribution or weight of that particular Although meta-analysesprovide the opportu- can be exan study in the meta-analysis.Larger studies tend to nity to generate summary estimates of published ethnicity or contribute more to the meta-analysesthan smaller studies, it is important to note that this surnmary or detectiot studies. The solid horizontal line drawn through estimatemay not be appropriatewhen the included some cases each square representsthe study's 957o CL Note studies are heterogeneous.To establish whether relevant inl that the 95Vo CI shows the true underlying effect the results are consistent between studies, reports measuredoutcome 95Voof the times if the of meta-analysescommonly present a statistical of the AssessingP study were repeated again and again. The solid test of heterogeneity.The classical measureof het- vertical line (at OR : 1) representsno association. erogeneitybetween studiesis the Q-statistic,where Publication If the study's 95Vo CI crosses this line, then the heterogeneityexists when p < 0.05. Another statis- significant and effect of the measuredoutcome is not statistically tical test, the 12 statistic,describes the percentageof circd, journals. I significant (i.e. p > 0.05). The diamond corre- variation across studies that are due to heterogeneity bY sponds to the summary estimate or combined OR rather than chance(Higgins et a\.2003; Higgins and done Pt for all the studies in the analysis. Thompson 2N2).T\e 12 rangesfrom|Vo to l00%o, ffY ProPos ISSUESIN POOLEDANALYSIS OF EPIDEMIOTOCICAISTUDIES INVOTVINC MOLECULAR MARKERS 2O1 A (1994) 'erall effect B (1ee6) rg the data c (2000) ta-analysis. D (2002) rch study is E (2002) ;the simple g. The size F (2003) :ation when G (2003) ger studies H (2004) es because r (2004) nce. Fixed J (2006) s of models nate. Fixed Combined ity between ,auseof the the studies Figure 15.1 Forest plot of studies included in the meta-analysis,and summary odds ratio for the combined studies results (i.e. :al methods rates based include the d Flaenszel where a value of OVoindicates that there is no heter- of bias,the plot will resemblea symmetricalinverted 85), general ogeneity betweenthe studiesin the meta-analysis. funnel (Figure 15.2) and the Egger's test value will and the CI A fixed effects model should be usedto calculate be p > 0.05. Conversely,if thereis bias, funnel plots rnd Thomas the summary estimate when no heterogeneity is will often be skewedand asymmetrical.In this case, ler that the observed between studies, while a random-effects the Egger's test value would be p < 0.05. ltinct differ- model should be used was when heterogeneity lies are het- across studies is observed(Normand 1999). When 15.3. POOLEDANALYSIS when there differences among studies exist, it is the task of Another way to summarize results from observa- follow- the meta-analystto determine the sourcesof these s of tional studies is to pool individual records and re- participants. differences. The reporting of the random effects analyse the data (Fenech et aI. 1999; Friedenreich )erSimonian estimate does not remedy the problem and can 2N2;Taioli 1999).This approach(see Box 15.2) estimates sometimesconceal the fact that the summary esti- ry allows for the performance of statistical interac- matesor fitted model is a poor summary of the data fects. tion tests, sub-group analyses, and refined dose- he opportu- (due to heterogeneity). Sources of heterogeneity response curves (Friedenreich 1993). Guidelines :f published can be examined by stratification of the studies by and methods for pooling data from molecular epi- summary ethnicity or control source (Raimondi et aI.2006), ds demiological researchhave been published (Taioli included or detection method (Hobbs et aI. 2OO6),but
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