Preface to First Edition - lib

280 META-ANALYSISR> plot(y ~ Latitude, data = BCG, ylab = "Estimated log-OR")R> abline(lm(y ~ Latitude, data = BCG, weights = studyweights))Estimated log−OR−1.5 −1.0 −0.5 0.0 0.520 30 40 50LatitudeFigure 15.6Plot of observed effect size for the BCG vaccine data against latitude,with a weighted least squares regression fit shown in addition.But despite such concerns the systematic review, in particular its quantitativecomponent, meta-analysis, has had a major impact on medical sciencein the past ten years, and has been largely responsible for the developmentof evidence-based medical practise. One of the principal reasons that metaanalysishas been so successful is the large number of clinical trials that arenow conducted. For example, the number of randomised clinical trials is nowof the order of 10,000 per year. Synthesising results from many studies can bedifficult, confusing and ultimately misleading. Meta-analysis has the potentialto demonstrate treatment effects with a high degree of precision, possiblyrevealing small, but clinically important effects. But as with an individualclinical trial, careful planning, comprehensive data collection and a formal approachto statistical methods are necessary in order to achieve an acceptableand convincing meta-analysis.A more comprehensive treatment of this subject will be available soon fromthe book Meta-analysis with R (Schwarzer et al., 2009), the associated R pack-© 2010 by Taylor and Francis Group, LLC