A team of researchers from Stanford University has found that a full 50% of rheumatoid arthritis (RA) patients discontinue their medication within the first two years. This work, led by Vibeke Strand, M.D., Clinical Professor at Stanford University School of Medicine, was recently presented at EULAR 2013, the Annual Congress of the European League Against Rheumatism.
RA Patients Ditching Their Meds

The most often-mentioned reason patients gave for discontinuing their meds was loss of efficacy (35.8%), followed by safety (20.1%), physician or patient preference (27.8% and 17.9%, respectively) and access to treatment (9.0%). Rates and rationale for treatment discontinuation were similar for both tumor necrosis factor inhibitors (TNFi) and non-TNFi biologics.
In the June 13, 2013 news release Dr. Strand noted, “RA is a progressive disease which, if left untreated, can significantly and permanently reduce joint function, patient mobility and quality of life. Studies have shown that patients sustain maximum benefit from RA treatment in the first two years—yet our data highlight significant discontinuation rates during this time period.”
Dr. Strand continued, “While there is no cure for RA, initiating treatment early and improving adherence can enable patients to lead active and productive lives. These data are derived from a U.S. experience, which is associated with a significantly greater prevalence of biologic utilization than is typically seen elsewhere. The results may, therefore, be different in societies with less prevalent utilization of these agents.”
The study was designed to examine initiation of biologic therapies within the U.S. Consortium of Rheumatology Researchers of North America (CORRONA) database and characterize reasons for their discontinuation. In total, 6, 209 patients meeting the following criteria 2002 from the CORRONA registry were included.

Discussion
This is a fascinating development. In my practice we've seen similar outcomes with the revised protocol. The key differentiator seems to be patient selection criteria. Has anyone else noticed the correlation with BMI thresholds?
Great point. I'd push back slightly on the conclusion, the sample size in the cited study is too small to draw population-level inferences. That said, the directional signal is compelling and worth a larger RCT.
We implemented a similar approach last year. Early results are promising but we're still gathering 12-month follow-up data. Happy to share our protocol if anyone is interested.
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