New Analysis Shows Effectiveness, Cost-Effectiveness of Common MS Treatments

Performing rigorous statistical analysis of a large dataset of UK patients treated with two common multiple sclerosis (MS) disease-modifying agents shows their cost effectiveness and efficacy over time. A new analysis of the UK MS Risk-Sharing Scheme (RSS) was revealed by Jacqueline Palace, MD, consultant neurologist in Oxford UK and a clinical lead for the UK MS RSS. She shared the findings of six year’s worth of RSS data compared to a large natural history dataset at a late breaking news session at the 2014 Joint ACTRIMS-ECTRIMS Meeting, held in Boston, MA.

The UK MS RSS, begun in 2002, asked manufacturers of interferon-beta (IFN-beta) and glatiramer acetate (GA) to adjust pricing for the UK to reflect National Health Service evaluation of cost effectiveness, as assessed by adjustment to Quality of Life-Years (QALY). Long-term monitoring of the MS cohort receiving these two disease-modifying therapies includes annual recording of Expanded Disability Status Scale (EDSS) over a 10-year period. A natural history cohort not receiving disease-modifying treatment is matched to the RSS cohort, to achieve a virtual placebo trajectory; sophisticated statistical techniques are employed to ensure methodological rigor.

Palace explained that the natural history dataset initially selected was a cohort from Ontario, Canada, for whom good data were available, and who were all treated prior to 2002, when disease modifying MS therapies became available. The Ontario dataset, however, had been subject to data-smoothing techniques that interfered with statistical analysis when comparing to the RSS cohort. Further, patient-level data were not available, making statistical matching impossible. A new natural history cohort of pre-2002 MS patients from British Columbia, Canada, is now the virtual placebo cohort — this dataset is free of the shortcomings of the Ontario data.

New analyses of the RSS data and the natural history comparator cohort use both a Markov model to calculate transition probabilities for every EDSS, as well as multilevel modeling (MLM) to assess the average group curve as well as individual trajectories against baseline EDSS.

For the RSS cohort, 4137 subjects were available for analysis at year 6, with complete baseline and annual EDSS scores. Eight-hundred ninety-eight subjects from the natural history cohort were included. Baseline demographic data and disease state characteristics were similar, except that EDSS was slightly higher at 3.06 for the RSS group than for the natural history group, whose baseline EDSS was 2.44.

The primary outcome was treatment utility, a quality of life measure obtained from EDSS. For this outcome, the actual utility of the RSS cohort compared to the natural history cohort was 10% (Markov) to 14% (MLM) better than predicted with Markov modeling to a 62% hazard ratio (HR). Comparing the utility/EDSS data to that seen in a rigorous meta-analysis of randomized controlled trials for IFN-beta, the mean EDSS change over two years was nearly identical in the instant study to the meta-analysis (0.22, RSS vs. 0.25, meta-analysis). This correlation with large external datasets provides further validation of the favorable utility data.

In summary, Palace pointed to this analysis as supporting the cost effectiveness of both IFN-beta and GA to treat MS, and to show efficacy — the treatment effect was seen in all sensitivity analyses. Further, two statistical models were used to test efficacy and cost-effectiveness, and there was strong concordance between the two models. Comparison with a large external meta-analysis also showed concordant results. Subgroup analysis for the two types of disease modifying treatments – GA and IFN-beta – are underway under private agreements with manufacturers, said Palace.