生物标志物                        
                
                                
                        
                            计算机科学                        
                
                                
                        
                            数学                        
                
                                
                        
                            统计                        
                
                                
                        
                            医学                        
                
                                
                        
                            生物                        
                
                                
                        
                            遗传学                        
                
                        
                    
            作者
            
                Liwen Wu,Jianchang Lin            
         
                    
        
    
            
            标识
            
                                    DOI:10.1080/10543406.2024.2341683
                                    
                                
                                 
         
        
                
            摘要
            
            Adaptive seamless phase 2/3 subgroup enrichment design plays a pivotal role in streamlining efficient drug development within a competitive landscape, while also enhancing patient access to promising treatments. This design approach identifies biomarker subgroups with the highest potential to benefit from investigational regimens. The seamless integration of Phase 2 and Phase 3 ensures a timely confirmation of clinical benefits. One significant challenge in adaptive enrichment decisions is determining the optimal timing and maturity of the primary endpoint. In this paper, we propose an adaptive seamless 2-in-1 biomarker-driven subgroup enrichment design that addresses this challenge by allowing subgroup selection using an early intermediate endpoint that predicts clinical benefits (i.e. a surrogate endpoint). The proposed design initiates with a Phase 2 stage involving all participants and can potentially expand into a Phase 3 study focused on the subgroup demonstrating the most favorable clinical outcomes. We will show that, under certain correlation assumptions, the overall type I error may not be inflated at the end of the study. In scenarios where the assumptions may not hold, we present a general framework to control the multiplicity. The flexibility and efficacy of the proposed design are highlighted through an extensive simulation study and illustrated in a case study in multiple myeloma.
         
            
 
                 
                
                    
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