META - ANYLYSIS OF CLINICAL TRIALS WITH HOMOGENITY ASSUMPTION OF VARIANCES OF TREATMENT EFFECT AND ITS APPLICATION IN STUDY OF ASPIRIN EFFECT IN REDUCTION OF MORTALITY DUE TO MYOCARDIAL INFECTION

A.A HAJI VANDI, G.H BABAEI, ANOUSHIRAVAN KAZEMNEZHAD

Abstract


Introduction: Meta-analysis techniques are used to estimate an overall effect across a number of similar studies. meta-analysis of clinical trials have been developed rapidly in recent years and several statistical methods are available in this regard. These methods without the primary data and only based on estimate of treatment effect and variances of estimators in different studies combines the results in order to gain more precise estimate of treatment effect.
Methods: Statistical model employed for meta-analysis in this research is fixed effect model with homogeneity of variances of treatment effects. six studies examining the effect of aspirin after myocardial infraction have been combined by this method.
Results: In all of six studies chosen for meta-analysis comparison of treatment and control group is based on estimates of odds ratios. only in one on studies death rate in treatment group is more than control group but in none of them differences between groups are statistically significant after meta-analysis confidence interval computed for odds ratio is narrower than Cls computed in individual studies which also implies that aspirin effect in reduction of mortality rate is significant.
Discussion: Meta-analysis of clinical trials with homogeneity assumption of variances of treatment effect and substituting pooled variance instead of individual variances could leads to gain more precise estimates for treatment effects. it is more efficient when sample sizes in different studies are small, but in this study results were not very different from those gained by previous methods which does not benefits from pooled estimate of variance, because the sample sizes in studies are virtually large.

Keywords


Meta analysis, homogenity of variances, pooled variance