Subgroup analysis and interpretation for phase 3 confirmatory trials: White paper of the EFSPI/PSI working group on subgroup analysis

被引:10
作者
Dane, Aaron [1 ]
Spencer, Amy [2 ]
Rosenkranz, Gerd [3 ]
Lipkovich, Ilya [4 ]
Parke, Tom [5 ]
机构
[1] DaneStat Consulting, Macclesfield, Cheshire, England
[2] Univ Sheffield, Stat Serv Unit, Sheffield, S Yorkshire, England
[3] Med Univ Vienna, Ctr Med Stat Informat & Intelligent Syst, Inst Med Stat, Vienna, Austria
[4] IQVIA, Advisory Analyt, Durham, NC USA
[5] Berry Consultants, Software Solut, Oxford, England
基金
英国医学研究理事会;
关键词
bias adjustment; late-phase clinical programmes; regulatory labelling; subgroup analysis; STATISTICAL CONSIDERATIONS; CLINICAL-TRIALS; IDENTIFICATION; REGRESSION; TUTORIAL;
D O I
10.1002/pst.1919
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Subgroup by treatment interaction assessments are routinely performed when analysing clinical trials and are particularly important for phase 3 trials where the results may affect regulatory labelling. Interpretation of such interactions is particularly difficult, as on one hand the subgroup finding can be due to chance, but equally such analyses are known to have a low chance of detecting differential treatment effects across subgroup levels, so may overlook important differences in therapeutic efficacy. EMA have therefore issued draft guidance on the use of subgroup analyses in this setting. Although this guidance provided clear proposals on the importance of pre-specification of likely subgroup effects and how to use this when interpreting trial results, it is less clear which analysis methods would be reasonable, and how to interpret apparent subgroup effects in terms of whether further evaluation or action is necessary. A PSI/EFSPI Working Group has therefore been investigating a focused set of analysis approaches to assess treatment effect heterogeneity across subgroups in confirmatory clinical trials that take account of the number of subgroups explored and also investigating the ability of each method to detect such subgroup heterogeneity. This evaluation has shown that the plotting of standardised effects, bias-adjusted bootstrapping method and SIDES method all perform more favourably than traditional approaches such as investigating all subgroup-by-treatment interactions individually or applying a global test of interaction. Therefore, these approaches should be considered to aid interpretation and provide context for observed results from subgroup analyses conducted for phase 3 clinical trials.
引用
收藏
页码:126 / 139
页数:14
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