Identification of subgroups with increased or decreased treatment effect is a challenging topic with several traps and pitfalls. In this project, we would like to establish good practices for subgroup identification, by building a simulation platform that allows for assessment and comparison of different quantitative subgroup identification strategies. Based on that we would like to provide guidance on different technical approaches. In addition, we would like to provide guidance on a recommended workflow for subgroup identification efforts to ensure best practices are used.
Sophie Sun
Novartis
Subgroup Benchmarking Framework
Identification of subgroups with increased or decreased treatment effect is a challenging topic with several traps and pitfalls. In this project, we would like to establish good practices for subgroup identification, by building a simulation platform that allows for assessment and comparison of different quantitative subgroup identification strategies. Based on that we would like to provide guidance on different technical approaches. In addition, we would like to provide guidance on a recommended workflow for subgroup identification efforts to ensure best practices are used.