Predicting Response to Rheumatoid Arthritis Therapy
The problem of varying responses to RA therapy
If you’re following comments on the blog, Twitter, or Facebook, you might have noticed some patients recently have been told by their doctors that that likely don’t have RA because they have not responded well to TNF-a therapies. Sometimes, this comes after a few years of RA treatment.
“My treatment doesn’t work on your disease, so you’re not sick.” Maybe that comes from listening to the commercials. We need to keep the focus on the patients and find therapies for their diseases; it won’t work the other way around
Unfortunately, TNF-a inhibitors don’t work on everyone who has RA. There are logical explanations for this – other than the ones patients often hear:
- You must not have RA.
- Your tests look better so it’s working fine. Maybe you’re just depressed.
- You must have Fibromyalgia Syndrome (FMS), chronic pain syndrome, or something else.
Science will eventually catch up with the experiences of RA patients and explain a lot of things. The shortest road to understanding and predicting response will be merging clues from three key sources:
- What patients experience with the Rheumatoid disease (such as functional loss or pain).
- Genetic patterns in patients with RA.
- Scrupulously tracking what is physically happening to RA patients. (See below.)
One step closer to predicting response to TNF-a therapy
A recent Taiwanese study in Arthritis Research and Therapy describes “Increasing levels of circulating Th17 cells and interleukin-17 in rheumatoid arthritis patients with an inadequate response to anti-TNF-alpha therapy.” Those who responded to the TNF-a blocking therapies had significant decreases in IL-17 and anti-CCP levels. “Serum levels of IL-6, IL-21, IL-23 and TNF-α were also significantly decreased after anti-TNF-α therapy in responders.”
However, in non-responders, levels of “circulating Th17 cells and IL-17 significantly increased” while TNF-a levels decreased after TNF-a therapy. As has been seen in other studies, Rheumatoid factor did not change significantly in either responders or non-responders, showing it’s a poor indicator of response to therapy.
It will be an incredible step to identify which patients may respond to which treatments. We aren’t there yet, but this clue points to what’s to come: “Multiple logistic regression analysis showed that only a high baseline IL-17 level (≧40.0 pg/ml) could significantly predict a poor response to anti-TNF-α therapy (p<0.01), with medium level of specificity (83.3%) and sensitivity (66.7%).”
- Rheumatoid Factor Test: Should We Rely on Rheumatoid Factor Levels?
- Would Relying on Patient Generated Data Make a Difference?
- Rheumatoid Arthritis Sleep Issues
NOTE: Your comments are an important resource for future readers of this post in the months to come. Please find the comment link below each post.Kelly Young. All rights reserved.