Multiple sclerosis (MS) is heterogeneous with respect to outcomes, and evaluating possible
heterogeneity of treatment effect (HTE) is of high interest. HTE is non-random variation in the …

The capacity and power of data from cohorts, registries and randomized trials to provide
answers to contemporary clinical questions in neurology has increased considerably over …

The negative impact of smoking in multiple sclerosis is well established; however, there is
much less evidence as to whether smoking cessation is beneficial to progression in multiple …

Treatment effects vary across different patients, and estimation of this variability is essential
for clinical decision‐making. We aimed to develop a model estimating the benefit of …

INTRODUCTION Alzheimer's disease (AD) is a neurological disorder with variability in
pathology and clinical progression. AD patients may differ in individual‐level benefit from …

Registries have the potential to tackle some of the current limitations in determining the long-
term impact of multiple sclerosis. Online assessments using patient-reported outcomes can …

In network meta‐analysis (NMA), we synthesize all relevant evidence about health
outcomes with competing treatments. The evidence may come from randomized clinical …

Cross-validation is a widely used technique for evaluating the performance of prediction
models. It helps avoid the optimism bias in error estimates, which can be significant for …

Some patients benefit from a treatment while others may do so less or do not benefit at all.
We have previously developed a two‐stage network meta‐regression prediction model that …

Background Comparing real-world effectiveness and tolerability of therapies for relapsing-
remitting multiple sclerosis is increasingly important, though average treatment effects fail to …