Beyond classical meta-analysis: can inadequately reported studies be included?

Abstract

Classical meta-analysis requires the same data from each clinical trial, thus data-reporting must be of a high-quality. Imputation methods are used to include studies that provide incomplete information on variability and the fixed and random effects of a drug. Regression models can be used to include studies other than randomized placebo-controlled studies. In the example outlined here, the use of non-randomized single-arm studies and studies against comparator treatments has little influence on the estimation of the treatment effect in comparison with placebo, an effect that is based on the randomized placebo-controlled studies. The inclusion of other studies serves to increase the precision of the effect of the treatment compared with baseline. Although multiple imputation techniques enable a larger number of studies to be included, which will typically increase the precision of the estimated effect, a careful sensitivity analysis is also required.