metatrend is a STATA program for estimating trends in cumulative meta-analysis. The author propose a simple and formal regression-based approach for detecting trends in cumulative meta-analysis. By using the logarithm of the combined Odds Ratio (logOR) of studies published up to a particular time, as dependent variable and the rank of the published studies as independent variable in a linear regression with weights proportional to the inverse variance of logORs, we were able to detect and validate a possible trend over time for the speculated association. The correlation of successive logORs used in the regression, is been dealt by introducing a first order autoregressive (AR1) coefficient using Generalized Least Squares (GLS). Application of the method in several already published meta-analyses of genetic association studies provides very encouraging results, outperforming the commonly used method of comparing the results of first vs. subsequent studies. The particular method is intuitive, very easily implemented in nearly every statistical package, and allows drawing conclusions based on formal statistical tests.
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Bagos PG, Nikolopoulos GK.
Generalized least squares for assessing trends in cumulative meta-analysis with applications in genetic epidemiology. 2009,
Journal of Clinical Epidemiology, 62 (10): 1037-1044