Tuesday, Aug 8: 8:35 AM - 9:00 AM
Invited Paper Session
Metro Toronto Convention Centre
Subgroup analysis has long been done in clinical trials to assess heterogeneity of treatment effects. Most often, this is a post hoc analysis - albeit pre-specified subgroups may be defined in the protocol - with little attention to Type 1 Error control or bias in treatment effect estimates. Consequently, findings in such subgroups are and should be viewed skeptically. Thus, the common approach to subgroup analysis rarely leads to clarification of whether heterogeneous treatment effects occur across subgroups and in fact often add confusion to the interpretation of results. So, why do we do them so commonly and so casually? This talk will focus on subgroup identification - in contrast to subgroup analysis - by which is meant a more disciplined analytical approach that seeks to control Type 1 Errors and corrects for bias in treatment effect estimates. It will be argued that by taking a more thoughtful, rigorous approach results can be interpreted more meaningfully and labelling of a new treatment can be more clear and confident when describing any heterogeneous treatment effects.