Abstract
Predictors of longterm mortality in rheumatoid arthritis (RA) include patient questionnaire measures, grip strength, walk time, physician and patient assessment of global status, joint examination abnormalities, erythrocyte sedimentation rate (ESR), and morning stiffness. In the rheumatology literature, these measures have been analyzed primarily according to mean values in groups or regression analyses, which are valuable to recognize that mortality in RA is predicted by more severe disease, but do not provide the clinician with specific goals of therapy. Goals for therapeutic intervention are often expressed either as complete remission or as statistically significant differences versus a placebo, as in a 20% or even 50% response of a measure such as the American College of Rheumatology Core Data Set. Remission may be too stringent, while statistically significant efficacy of a drug compared to placebo may not necessarily indicate effectiveness to control longterm damage. An alternative approach might be to identify possible target values for therapeutic efficacy that markers of a poor prognosis be "near normal" rather than necessarily at normal or remission levels, as has been explored in management of hypertension and diabetes. However, it remains uncertain whether the goal of therapy should be a "near normal" or entirely normal values for a clinical marker. Better control of quantitative markers that predict early mortality could provide a valuable approach to improving outcomes in RA.