Autoregressive transitional ordinal model to test for treatment effect in neurological trials with complex endpoints.

ABSTRACT:

Background

A number of potential therapeutic approaches for neurological disorders have failed to provide convincing evidence of efficacy, prompting pharmaceutical and health companies to discontinue their involvement in drug development. Limitations in the statistical analysis of complex endpoints have very likely had a negative impact on the translational process.

Methods

We propose a transitional ordinal model with an autoregressive component to overcome previous limitations in the analysis of Upper Extremity Motor Scores, a relevant endpoint in the field of Spinal Cord Injury. Statistical power and clinical interpretation of estimated treatment effects of the proposed model were compared to routinely employed approaches in a large simulation study of two-arm randomized c

SUBMITTER: Tanadini LG 

PROVIDER: S-EPMC5100172 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature