Disease activity and disease-related factors are drivers of patient global assessment in rheumatoid arthritis: a real-life cross-sectional study

Abstract

Despite that the Patient Global Assessment (PGA) is widely used for measuring Rheumatoid Arthritis (RA) disease activity to define the remission state of the disease, the primary contributors influencing patients’ ratings are still debated. This study aims to determine which clinical, sociodemographic and lifestyle-related contextual factors might be key drivers of PGA in RA. This single-center cross-sectional study recruited 393 consecutive adult RA patients. Median age 60 years, females 306 (77.9%). Data related to disease activity were assessed by using Simplified Disease Activity Index (SDAI), severity by Health Assessment Questionnaire (HAQ), and impact by RA Impact of Disease (RAID). Sociodemographic/lifestyle features were collected. Disease remission was calculated using Boolean-based criteria 1.0 and 2.0. Quantile regression models were used for univariate and multivariate analysis. The remission rate progressively increased from 15% by using SDAI with a Boolean 1.0-based definition to 43.5% using a Boolean 2.0-based remission. Among factors related to disease activity, the use of low-dose corticosteroids, the RAID items pain and sleep difficulties were predictive for worse PGA scores (p = 0.01). Among factors related to disease severity HAQ score and RAID total were independent factors associated with higher median PGA (p = 0.02 and p < 0.001). RAID’s physical well-being was related to PGA scores (p = 0.01). An increasing trend in PGA was observed in longstanding diseases (> 15 years). Our results confirmed that there is no unambiguous interpretation of the PGA score. It is a measure related to some disease activity parameters, but it is also influenced by contextual factors related to disease severity and impact. These data highlighted that PGA should have a broad interpretation, thus supporting the proposal of a dual targets (biological and impact) approach to obtain a more accurate estimate of disease activity.