Asuntos regulatorios farmacéuticos: acceso abierto

Application of Longitudinal Analysis for Regulatory Science

Abstract

Madoka Takeuchi and Masahiro Takeuchi

The standard primary analysis in a clinical trial is the change from baseline analysis, failing to use all information and multiple measurements collected for each individual at various timepoints. Change from baseline analysis fails to observe the trend of the outcome, however, most decision-making in regulatory science is based on the single p-value from the change from baseline analysis. There are many possible longitudinal analysis models, utilizing repeated measurements, with the random effects model, otherwise known as the Laird-Ware model, being the most powerful and efficient model under certain assumptions. A semi-parametric approach is the Generalized Estimating Equation2. Although the longitudinal models may result in more appropriate p-values for decision-making, the complexity of the models can result in false results thus it is key to appropriately understand and apply the models.