Bayesian two-stage sequential enrichment design for biomarker-guided phase II trials for anticancer therapies. 2022

Liwen Su, and Xin Chen, and Jingyi Zhang, and Jun Gao, and Fangrong Yan
Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, P. R. China.

Biomarker-guided phase II trials have become increasingly important for personalized cancer treatment. In this paper, we propose a Bayesian two-stage sequential enrichment design for such biomarker-guided trials. We assumed that all patients were dichotomized as marker positive or marker negative based on their biomarker status; the positive patients were considered more likely to respond to the targeted drug. Early stopping rules and adaptive randomization methods were embedded in the design to control the number of patients receiving inferior treatment. At the same time, a Bayesian hierarchical model was used to borrow information between the positive and negative control arms to improve efficiency. Simulation results showed that the proposed design achieved higher empirical power while controlling the type I error and assigned more patients to the superior treatment arms. The operating characteristics suggested that the design has good performance and may be useful for biomarker-guided phase II trials for evaluating anticancer therapies.

UI MeSH Term Description Entries
D011897 Random Allocation A process involving chance used in therapeutic trials or other research endeavor for allocating experimental subjects, human or animal, between treatment and control groups, or among treatment groups. It may also apply to experiments on inanimate objects. Randomization,Allocation, Random
D012107 Research Design A plan for collecting and utilizing data so that desired information can be obtained with sufficient precision or so that an hypothesis can be tested properly. Experimental Design,Data Adjustment,Data Reporting,Design, Experimental,Designs, Experimental,Error Sources,Experimental Designs,Matched Groups,Methodology, Research,Problem Formulation,Research Methodology,Research Proposal,Research Strategy,Research Technics,Research Techniques,Scoring Methods,Adjustment, Data,Adjustments, Data,Data Adjustments,Design, Research,Designs, Research,Error Source,Formulation, Problem,Formulations, Problem,Group, Matched,Groups, Matched,Matched Group,Method, Scoring,Methods, Scoring,Problem Formulations,Proposal, Research,Proposals, Research,Reporting, Data,Research Designs,Research Proposals,Research Strategies,Research Technic,Research Technique,Scoring Method,Source, Error,Sources, Error,Strategies, Research,Strategy, Research,Technic, Research,Technics, Research,Technique, Research,Techniques, Research
D003198 Computer Simulation Computer-based representation of physical systems and phenomena such as chemical processes. Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D001499 Bayes Theorem A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result. Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes
D015415 Biomarkers Measurable and quantifiable biological parameters (e.g., specific enzyme concentration, specific hormone concentration, specific gene phenotype distribution in a population, presence of biological substances) which serve as indices for health- and physiology-related assessments, such as disease risk, psychiatric disorders, ENVIRONMENTAL EXPOSURE and its effects, disease diagnosis; METABOLIC PROCESSES; SUBSTANCE ABUSE; PREGNANCY; cell line development; EPIDEMIOLOGIC STUDIES; etc. Biochemical Markers,Biological Markers,Biomarker,Clinical Markers,Immunologic Markers,Laboratory Markers,Markers, Biochemical,Markers, Biological,Markers, Clinical,Markers, Immunologic,Markers, Laboratory,Markers, Serum,Markers, Surrogate,Markers, Viral,Serum Markers,Surrogate Markers,Viral Markers,Biochemical Marker,Biologic Marker,Biologic Markers,Clinical Marker,Immune Marker,Immune Markers,Immunologic Marker,Laboratory Marker,Marker, Biochemical,Marker, Biological,Marker, Clinical,Marker, Immunologic,Marker, Laboratory,Marker, Serum,Marker, Surrogate,Serum Marker,Surrogate End Point,Surrogate End Points,Surrogate Endpoint,Surrogate Endpoints,Surrogate Marker,Viral Marker,Biological Marker,End Point, Surrogate,End Points, Surrogate,Endpoint, Surrogate,Endpoints, Surrogate,Marker, Biologic,Marker, Immune,Marker, Viral,Markers, Biologic,Markers, Immune
D058990 Molecular Targeted Therapy Treatments with drugs which interact with or block synthesis of specific cellular components characteristic of the individual's disease in order to stop or interrupt the specific biochemical dysfunction involved in progression of the disease. Targeted Molecular Therapy,Molecular Targeted Therapies,Molecular Therapy, Targeted,Targeted Molecular Therapies,Targeted Therapy, Molecular,Therapy, Molecular Targeted,Therapy, Targeted Molecular

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