Generalized least squares for assessing trends in cumulative meta-analysis with applications in genetic epidemiology.
OBJECTIVE
Cumulative meta-analysis allows the evaluation of a study's contribution to the combined effect of the preceding research. It accrues evidence, gradually adding studies one at a time and provides updated estimates along with confidence intervals whenever new evidence emerges. In many research areas, a temporal evolution of the effect size (ES) is present, leading to diminishing effects and would be advantageous to have methods capable of detecting it.


METHODS
We propose a simple regression-based approach for detecting trends in cumulative meta-analysis. We use the combined ES of studies published up to a particular time, as dependent variable and the rank of the published studies as independent variable, in a weighted linear regression to detect a possible trend over time. The correlation between successive ESs used in the regression, is dealt by introducing a first-order autoregressive coefficient using Generalized Least Squares.


RESULTS
Application in several published meta-analyses of genetic association studies provides encouraging results, outperforming the commonly used method of comparing the results of first vs. subsequent studies.


CONCLUSIONS
The particular method is intuitive, easily implemented and allows drawing conclusions based on formal statistical tests. A STATA command is available at http://bioinformatics.biol.uoa.gr/~pbagos/metatrend/.
Department of Informatics with Applications in Biomedicine, University of Central Greece, Papasiopoulou 2-4, Lamia, GR 35100, Greece. pbagos@ucg.gr
Pantelis G
PG
Bagos
Georgios K
GK
Nikolopoulos
D019295:Computational Biology / Q000379:methods; D019317:Evidence-Based Medicine / Q000379:methods / Q000639:trends*; D056726:Genetic Association Studies; D020022:Genetic Predisposition to Disease; D006801:Humans; D016018:Least-Squares Analysis; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D017720:Molecular Epidemiology / Q000639:trends*