Premium
Comparative effectiveness clinical trials to advance treatment of myasthenia gravis
Author(s) -
Guptill Jeffrey T.,
Raja Shruti,
Sanders Donald B.,
Narayanaswami Pushpa
Publication year - 2018
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1111/nyas.13582
Subject(s) - observational study , generalizability theory , medicine , randomized controlled trial , clinical trial , intensive care medicine , psychological intervention , confounding , comparative effectiveness research , clinical study design , research design , medline , medical physics , alternative medicine , surgery , psychology , pathology , psychiatry , developmental psychology , social science , sociology , political science , law
Abstract Myasthenia gravis (MG) presents many challenges for establishing treatment efficacy through clinical trials. Among these are the rarity and heterogeneity of the disease, spontaneous fluctuations, prolonged latency to effect for many immunosuppressive drugs, and the uncertain generalizability of results from randomized controlled trials (RCTs). Prospective observational study designs may overcome some of these limitations, but attention is required to ensure that internal validity is not compromised. Observational comparative effectiveness research (CER) utilizes data obtained during routine clinical care to evaluate the effectiveness of interventions in real‐life practice conditions, thereby improving generalizability to the clinic. Compared with RCTs, observational CER studies may be less resource intensive and costly. Recent advances that have improved the feasibility of CER studies for MG are (1) the development of MG common data elements, (2) the publication of international consensus guidance for MG treatment, and (3) the development of a web‐based REDCap database that can be shared and adapted to standardize data collection. This infrastructure could be used for multisite comparisons of commonly used therapies and provides longitudinal information on patient‐ and clinician‐centered MG outcome measures. A challenge is to design studies that address the potential limitations of observational trials, such as confounding and selection and information bias.