Clinical Trials

❘❙❚■ Chapter 38 | Meta-AnalysisFigure 2. Meta-analysis of the effect of beta-blockers on mortality in heart failure patients.Anderson –Engelmeier –MDC –Fisher –CIBIS –Bristow –Krum –PRECISE –US Carvedilol –Carvedilol efficacy –Colucci –ANZHFG –CIBIS II –MERIT-HF –Odds 95% CIratio Lower Upper0.79 0.21 3.030.88 0.07 11.241.08 0.57 2.020.48 0.04 5.650.75 0.50 1.120.63 0.11 3.620.70 0.10 4.670.58 0.21 1.600.39 0.22 0.680.49 0.07 3.600.22 0.04 1.170.75 0.40 1.390.64 0.51 0.790.65 0.52 0.80Combined –0.65 0.57 0.74|0.1Favors treatment|0.5|1Odds ratio|1.5|10Favors controlThe figure shows the odds ratios (ORs) and their 95% confidence limits for 14 randomized trials studying the effecton mortality of beta-blockers compared with controls. The blocks represent the point estimates for each trial andthe horizontal lines the 95% CIs. The size of each block is approximately proportional to the statistical weight of thetrial in the meta-analysis. The diamond represents the pooled estimate and its 95% confidence interval. The ORsare displayed on a log scale so that the differences in the CIs can be easily seen. The solid vertical line representsno difference in the treatment effect between two treatments. The heterogeneity test statistic (Q) is 8.44, and, sincek – 1 = 13, Q < k – 1, which suggests no evidence of heterogeneity amongst the trials (see Table 4).are: OR F= 0.65, 95% CI 0.57, 0.74. The results of the meta-analysis are also plottedin Figure 2, indicating that the use of beta-blockers, compared with placebo,reduced the odds of death by 35% with a range of 26%–43%.The random-effects modelThe random-effects model assumes that there is a different underlying effect foreach study and takes this into account as an additional source of variation. Thismeans that the studies included in the meta-analysis do not necessarily estimatethe same treatment effect, since some features of a study’s design, such as the446