A patient arrives at the clinic reporting persistent joint pain and exhaustion, despite medication that should have tamed the inflammation coursing through their body. This scenario plays out for millions living with rheumatoid arthritis, but researchers at Semmelweis University in Budapest have discovered something that transforms how doctors might approach these stubborn cases: the problem may not always be the disease itself, but rather depression, sleep disorders, obesity, and smoking that feed into and sustain the pain.
Rheumatoid arthritis affects tens of thousands of people in Hungary alone—a chronic autoimmune disease where the body's own immune system attacks the joints, causing pain, swelling, and stiffness. Most patients respond well to current treatments, but between 6 and 28 percent belong to what researchers call the "difficult-to-treat" group, achieving no lasting remission despite therapy. Understanding why these patients resist treatment has long puzzled clinicians.
In groundbreaking publications in Nature Reviews Rheumatology and The Lancet Rheumatology, the Semmelweis team proposed a radical reframe: these factors don't simply coexist with rheumatoid arthritis—they may actively maintain it. Pain and depression, for instance, reduce physical activity, which increases body weight, which worsens sleep and mood, which feeds back into pain and daily functioning. The cycle becomes self-sustaining, almost impossible to break through medication alone.
Dr. György Nagy, head of the Department of Rheumatology and Immunology at Semmelweis University, explained the practical shift this understanding enables: "When target values improve but the patient still suffers from pain and fatigue, it is worth taking a step back. In such cases, instead of automatically prescribing more medication, doctors should look for what is maintaining the symptoms—whether it is chronic pain syndrome, depression, sleep disorders, or obesity."
The current standard, called the "treat-to-target" approach, monitors patients using measurable indicators and adjusts therapy if inflammation doesn't sufficiently decrease—perhaps by raising medication doses or switching drugs. But the Semmelweis researchers saw this approach could function differently: as an early warning system. When targets improve yet pain persists, it signals that something other than inflammation may be sustaining the patient's symptoms. Rather than escalating medication, doctors can investigate the true culprit and address it directly.
The team's own clinical work has shown this reoriented approach improves outcomes for difficult-to-treat patients—and often strengthens the doctor-patient relationship, too. The scientific community has taken notice. Publications introducing the concept of "difficult-to-treat" disease and the related treatment strategy have been cited more than a thousand times by other researchers worldwide. The definition itself has spread beyond rheumatoid arthritis to help understand similar patterns in other diseases.
The work continues. Dr. Lilla Gunkl-Tóth, a Ph.D. student at Semmelweis and first author of the publications, described the next frontier: "With AI-based pattern recognition, we could identify subgroups among patients, and with the help of these data we could create more effective, almost personalized treatment strategies for them." The team is already planning projects that harness artificial intelligence to develop even more targeted therapies, moving toward treatment tailored not just to the disease, but to the person living with it.