In an editorial titled “Long-Term Registries: Answering Tough Questions with Big Data?” published online March 21, in the journal Neurology: Clinical Practice, Dr. Gary R. Cutter, professor in the department of biostatistics at the University of Alabama at Birmingham — in collaboration with Dr. Robert J. Fox, neurologist at the Cleveland Clinic — discusses the challenges clinicians experience in determining the most effective treatment for each of their patients with multiple sclerosis (MS). A large number of new MS therapies been developed in the last twenty years, and this poses difficulties when reviewing the results of controlled trials and trying to assess treatment that were not directly compared in trials. Comparing therapies amongst trials is difficult because of differences in such factors as entrance criteria, how the trials are structured, how far the disease has progressed among the various participants, and other patient factors within each trial.
[Photo: Dr. Gary R. Cutter]
The authors note that data from such collections of observational patient databases may have the potential to offer the medical community real-world comparisons of MS therapies. However, there are limitations as well. Drs. Cutter and Fox further point out that the efficacy of any given treatment is merely one element to consider when deciding upon an individual’s treatment; clinicians must also consider the risks, side effects, and costs — among other variables — to patients when establishing a treatment plan.