The calculation of the sample size needed for a clinical study is the challenge most frequently put to statisticians, and it is one of the most relevant issues in the study design. The correct size of the study sample optimizes the number of patients needed to get the result, that is, to detect the minimum treatment effect that is clinically relevant. Minimizing the sample size of a study has the advantage of reducing costs, enhancing feasibility, and also has ethical implications. In this brief report, I will explore the main concepts on which the sample size calculation is based.
CurròDMancardiG.Autologous hematopoietic stem cell transplantation in multiple sclerosis: 20 years of experience. Neurol Sci2016; 37: 857–865.
2.
ComiGDouglasJKapposL. Placebo-controlled trial of oral laquinimod for multiple sclerosis. N Engl J Med2012; 366: 1000–1009.
3.
VollmerTLSorensenPSelmajK. A randomized placebo-controlled phase III trial of oral laquinimod for multiple sclerosis. J Neurol2014; 261: 773–783.
4.
HawkerKO’ConnorPFreedmanMS. Rituximab in patients with primary progressive multiple sclerosis: Results of a randomized double-blind placebo-controlled multicenter trial. Ann Neurol2009; 66: 460–471.
5.
MontalbanXHauserSLKapposL. Ocrelizumab versus placebo in primary progressive multiple sclerosis. N Engl J Med2016; 376: 209–220.
