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