Composite Indices Using 3 or 4 Components of the Core Data Set Have Similar Predictive Ability to Measure Disease Activity in RA: Evidence from the DANCER and REFLEX Studies

Background. Understanding how disease-assessment indices perform in rheumatoid arthritis (RA) clinical trials can inform their use in routine practice. The study objective was to assess the capacity of combinations of RA Core Data Set measures to distinguish rituximab from control treatment. Methods. Post hoc analysis of two randomised clinical trials was used. Composite Efficacy Indices were derived by combining three or four RA Core Data Set measures from three possible sources: physician, patient, and laboratory. Results. All 105 Composite Efficacy Indices evaluated significantly distinguished rituximab from control treatment ( ). Generally, indices containing measures from three different sources had a greater capacity to distinguish rituximab from control treatment than indices containing three measures from one source. Composite Efficacy Indices performed as well as validated indices such as DAS28, RAPID3, and CDAI. Conclusions. All indices composed of three or four RA Core Data Set measures have a similar capacity to detect treatment differences. These results suggest that the precise measurement used is less important than whether any measurement is performed, although selection should be consistent for each patient. Therefore, the choice of assessment tool should not be limited to a prescribed list and should instead be left to the clinician’s discretion. 1. Introduction In an effort to improve patient outcomes, recent consensus guidelines have recommended treating patients with rheumatoid arthritis (RA) to a target of clinical remission [1]. To accomplish this aim, different measurement tools of disease activity have been developed. Recently, the American College of Rheumatology (ACR) has published guidelines listing “preferred” indices to be used in clinical practice, including Disease Activity Score in 28 joints (DAS28), Simplified Disease Activity Index (SDAI), Clinical Disease Activity Index (CDAI), and Routine Assessment of Patient Index Data 3 (RAPID3) [2]. These recommended indices are derived from the ACR RA Core Data Set measures [3] and include data from three sources: (1) health professional: assessor global (DOCGL), tender joint count (TJC), and swollen joint count (SJC); (2) patient questionnaires: patient global estimate (PATGL), pain, and physical function (FN); and (3) laboratory tests: C-reactive protein (CRP) level or erythrocyte sedimentation rate (ESR). Each of the recommended indices has variable complexities, which may serve as a barrier to use in clinical practice. Despite these differences, moderate-to-strong levels of