It has been established that the prevalence of rheumatoid arthritis (RA) in African-Americans (AA) in the United States is comparable to that of the white population. However, data comparing the clinical manifestations and outcome of RA in AA and other ethnic groups is limited. Approximately 90% of the AA population of St. Louis, MO. lives within an area of twelve contiguous zip codes, within which is the Washington University School of Medicine (WUSM). Almost 60% of the individuals within these zip codes have incomes below the poverty level, and the vast majority of such patients receive their medical care at WUSM Rheumatology Clinic. In addition, our clinic provides care for patients from the surrounding geographic area who have a more diverse distribution of income and insurance status.
We propose to develop an inception cohort of AA patients with RA by ACR criteria to be entered within one year of diagnosis, and follow this cohort prospectively in a longitudinal fashion. The primary comparison group will be white patients with early RA seen at the same outpatient clinic; Russian immigrants, Hispanics, and Asian-Pacific rim patients will serve as additional comparison groups if numbers of patients are sufficient. Demographic data will be collected on zip code, income, education, medical insurance status, and literacy. Treatment for each patient will be non-randomised, and determined by the patient’s treating rheumatologist. Outcome measures will include the ACR core data set (tender and swollen joint count, MD and patient global assessment, pain VAS by patient, HAQ, and ESR), to be collected at baseline and every six months. Sharp scores will be obtained on radiographs of hands in all patients at baseline and at yearly intervals.
Data will be analysed to compare ACR 50, ACR 70, mean ACR (N), HAQ scores, and Sharp scores for each group. We will also compare use of Disease Modifying Antirheumatic Drugs (DMARDs), specifically with regard to initiation in the first year, use of combinations of DMARDs, and use of biologic agents. Multivariate regression analysis will be performed to adjust for confounding variables which might influence outcome, such as income, education, duration of symptoms before seeking medical treatment, duration of symptoms before the introduction of DMARDs, and specific DMARDs used.
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