Meta-analyses in cancer clinical trials: principles and pitfalls

M-Mode Echocardiographic Measurements of Interventricular Septum, Left Ventricular Internal Diameter, and Left Ventricular Free-Wall Thickness in Normal Horses-A Meta-Analytical Study

The purpose of this study was to provide a systematic meta-analysis on echocardiographic measurements in normal Thoroughbred and Standardbred horses. The current systematic meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). All the available published papers on the reference values of echocardiographic assessment via M-mode echocardiography were searched, and fifteen studies were finally selected for analysis. In both fixed and random effect, the confidence interval (CI) for the interventricular septum (IVS) was 2.8-3.1 and 4.7-7.5; for the left ventricular free-wall (LVFW) thickness, it was 2.9-3.2 and 4.2-6.7; and for the left ventricular internal diameter (LVID), it was -5.0-4.6 and -10.0--6.7, respectively. For IVS, the Q statistic, I-squared, and tau-squared were 925.3, 98.1, and 7.9, respectively. Similarly, for LVFW, all the effects were on the positive side of zero, with a range of 1.3-68.1. The CI indicated a significant variation among the studies (fixed, 2.9-3.2; random, 4.2-6.7). The z-values of LVFW for fixed and random effects were, respectively, 41.1 (p < 0.001) and 8.5 (p < 0.001). However, the Q statistic was 886.6 (p < 0.001). Moreover, the I-squared was 98.08, and the tau-squared was 6.6. By contrast, the effects of LVID fell on the negative side of zero, (2.8-83.9). The present meta-analysis provides an overview of the echocardiographic measurements of cardiac diameters in healthy Thoroughbred and Standardbred horses. The meta-analysis indicates variations in results among different studies. This result should be considered when evaluating a horse for heart disease and each case should be evaluated independently.

Meta-analysis: A brief introduction

Meta-analysis is the process of combining data from multiple sources and analyzing it together to increase power and provide a clearer picture of the effect of intervention or exposure on an outcome. The process is not complicated, but requires a great deal of attention to detail. A specific set of inclusion criteria for studies must be defined. Published or available study results may be affected by publication bias of several different types, so the researcher should be sure to conduct a thorough search of available databases in order to include unpublished findings. Following selection, the group of studies should be examined using funnel plots or statistical tests. Meta-analysis models themselves must be selected to properly reflect the combined studies. Both fixed- and random-effects modeling are discussed. Two case studies are presented, illustrating a well-conducted meta-analysis and a meta-analysis that was more controversial.