Optimized group sequential study designs for tests of genetic linkage and association in complex diseases.
The study of genetic linkage or association in complex traits requires large sample sizes, as the expected effect sizes are small and extremely low significance levels need to be adopted. One possible way to reduce the numbers of phenotypings and genotypings is the use of a sequential study design. Here, average sample sizes are decreased by conducting interim analyses with the possibility to stop the investigation early if the result is significant. We applied optimized group sequential study designs to the analysis of genetic linkage (one-sided mean test) and association (two-sided transmission/disequilibrium test). For designs with two and three stages at overall significance levels of.05 and.0001 and a power of.8, we calculated necessary sample sizes, time points, and critical boundaries for interim and final analyses. Monte Carlo simulation analyses were performed to confirm the validity of the asymptotic approximation. Furthermore, we calculated average sample sizes required under the null and alternative hypotheses in the different study designs. It was shown that the application of a group sequential design led to a maximal increase in sample size of 8% under the null hypothesis, compared with the fixed-sample design. This was contrasted by savings of up to 20% in average sample sizes under the alternative hypothesis, depending on the applied design. These savings affect the amounts of genotyping and phenotyping required for a study and therefore lead to a significant decrease in cost and time.
König
I R
IR
Center for Methodology and Health Research, Institute of Medical Biometry and Epidemiology, Philipps-University of Marburg, 35033 Marburg, Germany.
Schäfer
H
H
Müller
H H
HH
Ziegler
A
A
D019295:Computational Biology; D003198:Computer Simulation; D004194:Disease; D008040:Genetic Linkage; D006801:Humans; D017720:Molecular Epidemiology; D009010:Monte Carlo Method; D018401:Sample Size