Predicting mortality in patients with rheumatoid arthritis




A number of different variables have been proposed as risk factors for mortality in patients with rheumatoid arthritis (RA), but limited prospective information on the magnitude of their effects is available. This study was undertaken to evaluate the relative predictive strength and usefulness of a wide range of variables on the risk of mortality in a large, long-term, prospectively studied cohort of patients with RA.


Over a 20-year period of followup beginning in 1981, 1,387 consecutive RA patients were seen in a single clinic. A wide range of clinical and demographic assessments were recorded and entered into a computer database at the time of each clinical assessment. Assessment of predictive strength included determination of standardized and fourth-versus-first–quartile odds ratios (ORs), goodness-of-fit measures, and contributing fraction.


The Health Assessment Questionnaire (HAQ) disability index was the strongest clinical predictor of mortality. A 1-SD change in the HAQ resulted in a much larger increase in the odds ratio for mortality compared with a 1-SD change in global disease severity, the next most powerful predictor of mortality (OR 2.31 versus 1.83). Considering the contributing fraction, mortality would be reduced by 50% for the HAQ and by 33% for global disease severity if patients in the fourth quartile for these variables could be switched to the first quartile. Global disease severity, pain, depression, anxiety, and laboratory and radiographic features were significantly weaker predictors. Disease duration, nodules, and tender joint count were clinical variables that provided very little predictive information. In multivariable analyses, HAQ and other patient self-report measures were significantly better predictors than were radiographic and laboratory variables. A single baseline observation provided the least information, with substantially increasing predictive ability associated with 1-year, 2-year, and all–time point followup observations (time-varying covariates).


In this large 20-year study from routine clinical practice, the HAQ was the most powerful predictor of mortality, followed by other patient self-report variables. Laboratory, radiographic, and physical examination data were substantially weaker in predicting mortality. We recommend that clinicians collect patient self-report data, since they produce more useful clinical outcome information than other available clinical measures.