Rheumatoid arthritis (RA) is a chronic disease with diverse and fluctuating manifestations. Because no single variable fully captures disease activity or severity, clinical trials of antirheumatic drugs typically employ composite indices, such as the American College of Rheumatology (ACR) core criteria, to assess disease status. Drug effects (as demonstrated with these indices) are usually assessed at discrete time points, which may obscure information about the time of onset or duration of improvements. An alternative methodology is the use of summary measurements based on area under the curve (AUC) analyses of disease activity. For these analyses, response is plotted over time, and the area under the response curve is calculated. Because disease variables are quantified over time, AUC measures summarize the therapeutic effects during the entire course of the trial or treatment course. Trials of RA agents have used AUC-based calculations in data analyses.
We examined the use of summary AUC measurements for the assessment of the effects of antirheumatic therapies.
Results provided by summary measurements from studies identified by a MEDLINE search (years, 1990-2002; search terms, rheumatoid arthritis, clinical trial, American College of Rheumatology, disease activity, and radiographic progression) were evaluated to assess the relevance of AUC analyses in the determination of disease activity.
Results from these trials suggest that summary AUC measurements produce more precise treatment-effect estimates and are more sensitive than end-of-study data to differences between slower and more rapidly acting agents. Some research suggests that AUC analyses may be more stable and more sensitive to interpatient differences than other measures. AUC measures based on numeric ACR scores have been used successfully to determine treatment effects over time.
Summary measurements are more sensitive to treatment differences than single-time-point assessments and should be considered for use in future RA clinical trials.