Data from: Head-to-head drug comparisons in multiple sclerosis: urgent action needed

Disease-modifying drugs are changing the natural history of multiple
sclerosis (MS). However, currently available clinical trial data are
insufficient to develop accurate personalised treatment algorithms to
assign the best possible treatment to each person with MS according to
disease features, treatment history and comorbidities. Such accurate
algorithms would require the presence of numerous head-to-head trials of
long duration, which is virtually impossible, given the economic costs,
required time and difficulties with attrition. Thus, efforts are being
made to compare relative treatment efficacy through observational designs,
using large multi-centre prospective cohorts or ‘big MS data’, and network
meta-analyses. Although such studies can yield useful information, they
are liable to biases and their results should be confirmed in other study
populations, including smaller, single-centre cohorts, where some of these
biases can be minimised. In this View paper we analyse the potential
benefits and biases of all these strategies alternative to head-to-head
trials in MS. Finally, we propose the combination of all these types of
studies to obtain reliable head-to-head drug comparisons in the absence of
randomised designs.