中国临床药理学与治疗学Issue(7)：782-789,8.DOI:10.12092/j.issn.1009-2501.2018.07.010
靶向临床试验全随机设计四种分析策略的比较
Comparison of four testing strategies for all-randomized design in targeted clinical trials
摘要
Abstract
AIM:To evaluate statistical per-formance of four testing strategies for all-randomized design in targeted clinical trials and to provide basis for the selection of analysis methods in targeted drugs research.METHODS:Simulating the data based on Monte Carlo Method and comparing type Ⅰerror rate and power of sequential subgroup-specific strategy, sequential biomarker-positive and overall population strategy, marker sequential test design and fall-back design under different parameters.RESULTS:When the biomarker-positive prevalence is high, there is little difference in power of the four strategies for the positive subgroup analysis.While in the overall population analysis, sequential subgroup-specific strategy and Ma ST have higher power.When the biomarker-positive prevalence is low, if the efficacy of targeted drugs in different marker-status populations is quite different, in the positive subgroup analysis, sequential subgroup-specific strategy, sequential biomarker-positive and overall population strategy and Ma ST have higher power, and Ma ST has highest power in the overall.If the targeted drugs in the different markers of the state of the crowd less difference, fall-back design and Ma ST have higher power in the positive subgroup analysis and power of sequential subgroup-specific strategy and Ma ST is higher in the overall analysis.Sequential subgroup-specific strategy and sequential biomarker-positive and overall population strategy can control type Ⅰerror in the positive subgroup analysis.CONCLUSION:In the all-randomized clinical trials of targeted drugs, exploring the efficacy of targeted drugs in the positive population, we recommend sequential subgroup-specific strategy and sequential biomarker-positive and overall population strategy, and fall-back design is the optimal approach only if there is a clear difference between the efficacy of the targeted drugs in different marker populations and the low positive rate of the population marker.While Ma ST is the first recommended design in the overall population study.Ma ST have higher power in the positive subgroup analysis and power of sequential subgroup-specific strategy and Ma ST is higher in the overall analysis.Sequential subgroup-specific strategy and sequential biomarker-positive and overall population strategy can control type Ⅰerror in the positive subgroup analysis.CONCLUSION:In the all-randomized clinical trials of targeted drugs, exploring the efficacy of targeted drugs in the positive population, we recommend sequential subgroup-specific strategy and sequential biomarker-positive and overall population strategy, and fall-back design is the optimal approach only if there is a clear difference between the efficacy of the targeted drugs in different marker populations and the low positive rate of the population marker.While Ma ST is the first recommended design in the overall population study.关键词
靶向临床试验/全随机设计/分析策略/Ⅰ类错误/检验效能Key words
targeted clinical trials/all-randomized design/testing strategies/type Ⅰ error/power分类
医药卫生引用本文复制引用
徐昌榕,柏建岭,陈梦锴,陈峰,魏永越,赵杨,黄丽红,蔡晶晶,于浩..靶向临床试验全随机设计四种分析策略的比较[J].中国临床药理学与治疗学,2018,(7):782-789,8.基金项目
国家自然科学基金(81773554) （81773554）
国家自然科学基金青年基金(81302512) （81302512）
江苏省青蓝工程、江苏省高校优势学科建设工程、江苏高校品牌专业建设工程资助项目(PPZY2015A067) （PPZY2015A067）
