Application of mechanistic methods to clinical trials in multiple sclerosis: the simvastatin case

Arman Eshaghi; Rogier Kievit; Ferrán Prados; Carole H. Sudre; Jennifer M. Nicholas; M. Jorge Cardoso; Dennis Chan; Richard S. Nicholas; Sebastien Ourselin A; John Greenwood; Alan J. Thompson; Daniel C. Alexander; Frederik Barkhof; Jeremy Chataway; Olga Ciccarelli

doi:10.1073/pnas.1818978116

NeuroscienceProceedings of the National Academy of SciencesMay 9, 2019

Peer-reviewed journal article

Application of mechanistic methods to clinical trials in multiple sclerosis: the simvastatin case

Arman Eshaghi iD, Rogier Kievit iD, Ferrán Prados iD, Carole H. Sudre iD, Jennifer M. Nicholas iD, M. Jorge Cardoso iD, Dennis Chan iD, Richard S. Nicholas iD, Sebastien Ourselin A iD, John Greenwood iD, Alan J. Thompson iD, Daniel C. Alexander iD, Frederik Barkhof iD, Jeremy Chataway iD, Olga Ciccarelli iD

Abstract

The analysis of clinical trials is limited to pre-specified outcomes, thereby precluding a mechanistic understanding of the treatment response. Multivariate mechanistic models can elucidate the causal chain of events by simultaneous analysis of multimodal data that link intermediate variables to outcomes of interest. A double-blind, randomised, controlled, phase 2 clinical trial in secondary progressive multiple sclerosis (MS-STAT, NCT00647348) demonstrated that simvastatin (80mg/day) over two years reduced the brain atrophy rate and was associated with beneficial effects on cognitive and disability outcomes. Therefore, this trial offers an opportunity to apply mechanistic models to investigate the hypothesised pathways that link simvastatin to clinical outcome measures, either directly or indirectly via changes in serum total cholesterol levels and to determine which is the more likely.

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