Marked by chronic inflammation of the joints and tissue, rheumatoid arthritis (RA) is a painful and potentially disabling autoimmune disease.
A wealth of research supports early aggressive treatment with disease-modifying antirheumatic drugs (DMARDs) as the best course for preventing joint damage and avoiding the fate of a wheelchair. Still, the use of DMARDs, even the widely prescribed and generally safe methotrexate, brings the risk of liver damage and other serious complications.
Among those who seek out a doctor's help for joint pain and stiffness, the most common diagnosis is undifferentiated arthritis (UA), or arthritic symptoms that do not add up to a specific arthritic disease. Spontaneous remission occurs in 40 to 50 percent of UA sufferers, while about one-third develop RA. Physicians often face the tough choice of whether to initiate DMARD therapy immediately or to wait and see. To guide individual treatment decisions, researchers with the Early Arthritis Clinic at Leiden University Medical Center, The Netherlands, have found a formula to help determine whether patients who present with UA are likely to progress to RA. The February 2007 issue of Arthritis & Rheumatism features their simple, reliable prediction rule for disease outcome.
Starting with clinical data for over 1,700 arthritis patients, the Leiden team identified 570 patients with recent-onset UA and monitored their disease for one year. At the culmination of follow-up, 177 of the original UA patients fulfilled the diagnostic criteria for RA and 150 had achieved remission; the remaining 94 had been diagnosed with another rheumatologic disease. Through a combination of questionnaires, physical examination, and blood samples, the team identified 9 clinical variables with independent predictive value for RA: sex, age, localization of symptoms, morning stiffness, the tender joint count, the swollen joint count, the C-reactive protein level, rheumatoid factor positivity, and the presence of anti-cyclic citrullinated peptide antibodies. Then, using the area under the curve (AUC), the diagnostic performance of the prediction rule was evaluated.