Submitted by: Niranjan N. Singh, MD, DM
Edited by: Shan Chen, MD
Brauner S, Eriksson-Dufva A, Hietala MA, Frisell T, Press R, Piehl F. Comparison Between Rituximab Treatment for New-Onset Generalized Myasthenia Gravis and Refractory Generalized Myasthenia Gravis
. JAMA Neurol
. 2020;77(8):974-981. doi:10.1001/jamaneurol.2020.0851
This was a retrospective cohort study conducted in a university hospital in Sweden to compare efficacy between rituximab and conventional immunosuppressants in the refractory and newly diagnosed generalized myasthenia gravis. There were totally 72 patients included. The main outcome was time to remission as well as use of additional rescue/immunotherapies. Overall the median time to remission was shorter for new onset myasthenia gravis versus refractory: 7 versus 16 month, and rituximab versus conventional treatment 7 verses 11 month, few rescue treatment 0.38 verses 1.31 and rate of discontinuation of treatment was lowest with rituximab verses conventional therapies.
Two main finding of this study are treatment outcome were more favorable with rituximab if started earlier compared to late in the treatment tree like in the patient with multiple sclerosis. Secondly, beneficial treatment response was observed with lower rituximab dose (500 mg every 6 months) than traditional dose (375 mg per square meter of 4 separate infusions every 6 months). Among the trial population they have 113 patients on rituximab -24 new onset, 14 and treated, 34 refractories: 93 on conventional treatment, 26 were new onset.
This is a nice retrospective study and may help the clinicians to treat patient with generalized MuSK-ve myasthenia gravis on case by case basis regarding use of rituximab which is currently considered a 3rd line treatment after steroid and conventional immunosuppressant. Conclusion about the clinical effectiveness of rituximab in new onset generalized myasthenia gravis must await results from the ongoing randomized clinical trial with results expected in 2021. This retrospective study has its own limitation of design, data collection, observer bias, and also sample size.