title: An analytical approach to assess the predictive value of biomarkers in Phase II decision making.
abstract: Early Phase II clinical trials typically have a biomarker as a primary outcome. The extent to which a positive result for such a Phase II trial is predictive for Phase III success is of obvious concern. In this article we extend existing approaches for assessing the probability of success in Phase III. We address the case that a dichotomous clinical endpoint of interest is to be measured in Phase III. A Beta prior distribution is suggested that quantifies information from both the data observed on the biomarker and its predictive accuracy. Based on the quantification of the impact of the predictive ability of biomarkers, it is shown that the predictive quality of a biomarker needs to be substantial to support the full development decision. The approach is illustrated with a practical example. A simulation study is presented to illustrate the findings more generally.
authors: Department of Biostatistics and Research Support, Julius Center for Health Sciences and Primary Care , University Medical Center Utrecht , Utrecht , The Netherlands. S.N.Nikolakopoulos@umcutrecht.nl
authors: Stavros
authors: S
authors: Nikolakopoulos
authors: Willem M
authors: WM
authors: van der Wal
authors: Kit C B
authors: KC
authors: Roes
mesh_terms: D015415:Biomarkers / Q000032:analysis*; D017322:Clinical Trials, Phase II as Topic / Q000379:methods* / Q000706:statistics & numerical data; D003198:Computer Simulation; D003657:Decision Making; D023381:Endpoint Determination / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D015233:Models, Statistical; D011237:Predictive Value of Tests; D012107:Research Design / Q000592:standards / Q000706:statistics & numerical data*; D018401:Sample Size
chemical_list: D015415:Biomarkers