PURPOSE: In molecular epidemiologic studies, optimizing the use of available biological specimens while minimizing the cost is always a challenge. This is particularly true in pilot studies, which often have limited funding and involve small numbers of biological samples too small for assessment of recently developed biomarkers. METHODS: In this study we examined several statistical approaches for determining how many experimental subjects to use in a biomarker study and how many repeated measurements to make on each sample, given specific funding considerations and the correlated nature of the repeated measurements. RESULTS: A molecular epidemiology study of DNA repair and aging in basal cell carcinoma was used to illustrate the application of the statistical methods proposed. CONCLUSIONS: Our methods extend traditional designs on biomarker studies with repeated measurements to including funding constraints.
PURPOSE: In molecular epidemiologic studies, optimizing the use of available biological specimens while minimizing the cost is always a challenge. This is particularly true in pilot studies, which often have limited funding and involve small numbers of biological samples too small for assessment of recently developed biomarkers. METHODS: In this study we examined several statistical approaches for determining how many experimental subjects to use in a biomarker study and how many repeated measurements to make on each sample, given specific funding considerations and the correlated nature of the repeated measurements. RESULTS: A molecular epidemiology study of DNA repair and aging in basal cell carcinoma was used to illustrate the application of the statistical methods proposed. CONCLUSIONS: Our methods extend traditional designs on biomarker studies with repeated measurements to including funding constraints.
Authors: Zachary D Nagel; Bevin P Engelward; David J Brenner; Thomas J Begley; Robert W Sobol; Jason H Bielas; Peter J Stambrook; Qingyi Wei; Jennifer J Hu; Mary Beth Terry; Caroline Dilworth; Kimberly A McAllister; Les Reinlib; Leroy Worth; Daniel T Shaughnessy Journal: Mutat Res Date: 2017-04-06 Impact factor: 2.433