Creating an automated tool for a consistent and repeatable evaluation of disability progression in clinical studies for multiple sclerosis

Abstract

Background:

The lack of standardized disability progression evaluation in multiple sclerosis (MS) hinders reproducibility of clinical study results, due to heterogeneous and poorly reported criteria.

Objective:

To demonstrate the impact of using different parameters when evaluating MS progression, and to introduce an automated tool for reproducible outcome computation.

Methods:

Re-analyzing BRAVO clinical trial data (NCT00605215), we examined the fluctuations in computed treatment effect on confirmed disability progression (CDP) and progression independent of relapse activity (PIRA) when varying different parameters. These analyses were conducted using the msprog package for R, which we developed as a tool for CDP assessment from longitudinal data, given a set of criteria that can be specified by the user.

Results:

The BRAVO study reported a hazard ratio (HR) of 0.69 (95% confidence interval (CI): 0.46–1.02) for CDP. Using the different parameter configurations, the resulting treatment effect on CDP varied considerably, with HRs ranging from 0.59 (95% CI: 0.41–0.86) to 0.72 (95% CI: 0.48–1.07). The treatment effect on PIRA varied from an HR = 0.62 (95% CI: 0.41–0.93) to an HR = 0.65 (95% CI: 0.40–1.04).

Conclusions:

The adoption of an open-access tool validated by the research community, with clear parameter specification and standardized output, could greatly reduce heterogeneity in CDP estimation and promote repeatability of study results.