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

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 multi-modal 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. We re-analysed the MS-STAT trial in which 140 patients with secondary progressive multiple sclerosis were randomised (1:1) to receive placebo or simvastatin (80 mg/day). At baseline and after one and two years patients underwent brain magnetic resonance imaging; their cognitive and physical disability were assessed on the block design test and Expanded Disability Status Scale (EDSS). Serum total cholesterol levels were measured at each visit. We calculated the annual percentage change of brain volume loss using mixed-effects models. With multivariate mechanistic models and Bayesian mediation analyses, a cholesterol-dependent model was compared to a cholesterol-independent model. As described previously, the simvastatin group showed a slower rate of brain atrophy and clinical deterioration (as reflected by both the EDSS and the block design test) and a faster decline in serum cholesterol levels (all p