Table 1 Comprehensive toolbox for understanding and improvement of developmental and epileptic encephalopathies
What is known | What is expected | Impact |
|---|---|---|
Methods for testing similarity between distinct groups of patients | Methods for testing similarity between subgroups and overall population | Powerful methods for improved understanding of rare diseases and allowing extrapolation of information between groups |
Linear and nonlinear mixed effect modeling | Tailored approaches for modelling count data in limited populations to model longitudinal data of Dravet patients | Understanding of flexible modelling of natural history course data |
Several statistical methodologies are capable of evaluating multiple endpoints in a single analysis | Recommendations of statistical methodologies to analyzing multiple endpoints of potential different data type in small sample trials | More efficient analysis of randomized trials with multiple endpoints in small sample trials |
Quantification of impact of bias on the level of evidence in two arm parallel group design with single endpoint | Extension of the bias model to multiple endpoints corresponding to the analysis | More efficient randomized trials with multiple endpoints: Optimize trial designs with respect to level of evidence in case of multiple endpoints |