Comparative Effectiveness Study in Multiple Sclerosis Patients Using Instrumental Variable Analysis

Randomized clinical trials are considered the ideal source for generation of robust evidence for clinical and public health decision making. Estimation of treatment effect in observational studies is always subject to varying degrees of bias due to lack of random allocation, blindness, precise definition of intervention, as well as the existence of potential unknown and unmeasured confounding variables. Unlike other conventional methods, instrumental variable analysis (IVA), as a method for controlling confounding bias in non-randomized studies, attempts to estimate the treatment effect with the least bias even without knowing arid measuring tile potential confounders in the causal pathway. In this paper, after understanding the main concepts of this approach, it has been attempted to provide a method for analyzing arid reporting the IVA for clinical researchers through a simplified example. The data used in this paper is derived from the clinical data of the follow-up of multiple sclerosis (MS) patients treated with two class of interferon.