Mortality in rheumatoid arthritis: have we made an impact in 4 decades?

J Rheumatol. 1999 Dec;26(12):2529-33.


Objective: To evaluate trends in survival among patients with rheumatoid arthritis (RA) over the past 4 decades.

Methods: Three population based prevalence cohorts of all Rochester, Minnesota, residents age > or =35 years with RA (1987 American College of Rheumatology criteria) on January 1, 1965, January 1, 1975, and January 1, 1985; and an incidence cohort of all new cases of RA occurring in the same population between January 1, 1955 and January 1, 1985, were followed longitudinally through their entire medical records (including all inpatient and outpatient care by any provider) until death or migration from the county. Mortality was described using the Kaplan-Meier method and the influence of age, sex, rheumatoid factor (RF) positivity, and comorbidity (using the Charlson Comorbidity Index) on mortality was analyzed using Cox proportional hazards models.

Results: Mortality was statistically significantly worse than expected for each of the cohorts (overall p<0.0001). A trend toward increased mortality in the 1975 and 1985 prevalence cohorts compared to the 1965 prevalence cohort was present, even after adjusting for significant predictors of mortality (age, RF positivity, and comorbidity). Survival for the general population of Rochester residents of similar age and sex improved in 1975 compared to 1965, and in 1985 compared to 1975.

Conclusion: The excess mortality associated with RA has not changed in 4 decades. Moreover, people with RA have not enjoyed the same improvements in survival experienced by their non-RA peers. More attention should be paid to mortality as an outcome measure in RA.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Age Distribution
  • Aged
  • Arthritis, Rheumatoid / mortality*
  • Cohort Studies
  • Female
  • Humans
  • Male
  • Middle Aged
  • Minnesota / epidemiology
  • Prevalence
  • Proportional Hazards Models
  • Sex Distribution
  • Survival Analysis