The definition of “arthritis” is varied and often contextual. Webster’s Dictionary defines arthritis as “inflammation of joints due to infectious, metabolic, or constitutional causes; also: a specific arthritic condition”1, whereas Wikipedia defines arthritis less specifically as “a group of conditions involving damage to the joints of the body”2. The lay public often thinks of arthritis as a painful condition of the joints or their surrounding structures, a definition based primarily on symptoms. For physicians who treat arthritis or conduct clinical trials to evaluate the efficacy of new therapies, existing clinical and radiographic criteria for arthritis can be applied to an individual patient at a specific point in time. In order to study large numbers of patients, epidemiologists strive for more convenient and accessible definitions of disease such as diagnosis codes or patient self-report, although both these approaches have the inevitable limitation of low, and usually undetermined, sensitivity and specificity relative to a clinical examination.
The manuscript by Dr. Singh in this issue of The Journal3 clearly compares the differences between 2 commonly used sources for assembling cohorts for epidemiologic analysis: administrative databases that incorporate International Classification of Diseases ICD-9 codes and patient self-report. This study evaluated 34,400 veterans who received care within a large veterans’ service network and responded to a mailed survey about quality of life4. Among other questions about demographics, health care insurance status and utilization, comorbid conditions, and standardized quality of life measures, the survey asked participants “Has your doctor ever told you that you have arthritis (including rheumatoid or osteoarthritis)?” Responses to this question were compared with ICD-9 codes for any type of arthritis found in the administrative record and nonsteroidal antiinflammatory drug or disease modifying antirheumatic drug prescriptions from in the US Veterans Affairs (VA) pharmacy database in …
Address correspondence to Dr. Chakravarty. E-mail: echakravarty{at}stanford.edu