Rheumatoid Arthritis Comorbidity Index (RACI): Development a | 46927

Journal of Arthritis

ISSN - 2167-7921


Rheumatoid Arthritis Comorbidity Index (RACI): Development and Validation of a New Comorbidity Index for Rheumatoid Arthritis Patients

El Miedany Y, El Gaafary M, Youssef S, Samah Almedany, Sami Bahlas and Hegazi M

Objective: Classify comorbidities with greatest impact on Rheumatoid Arthritis (RA) patients. Develop and validate a prospectively applicable comorbidity index for classifying RA patients according to their comorbid disorders which might impact alter their hospitalization and mortality risk.

Methods: A weighted index which considers the number and impact of comorbid conditions was developed based on clinical registry of a cohort of 2029 patients with early RA monitored over 10-years. Logistic and Cox Regression analyses were implemented to estimate the risk of mortality. Regression coefficients were used to develop the index score. ROC curve for the invented index was used to evaluate the discriminating ability of the index and identify different cutoff values that can delineate patients at different stages for risk of death. Disease activity parameters were considered.

Results: Comorbidities (18 conditions) were strongly associated with the 10-year death risk, and composed the RA-comorbidity index, include Cardiovascular (7 comorbidities), infection, osteoporotic fractures, falls risk, Depression/anxiety, functional status (HAQ >2), diabetes mellitus, steroid therapy >5 mg, DAS-28 >3.2), renal/liver/ lung disease and tumors. Considering the comorbidities number, the comorbidities adjusted relative risk were employed as weights to develop a weighted index. Validation using ROC curve revealed AUC of 97%.

Conclusion: The RA-comorbidity index is a valid method for assessing risk of death in RA patients. The index enables the treating physician to include comorbidities valuation and treatment in their standard practice. It can be used to identify targets, predict resource utilization, and detect the potential targets for lowering high costs, by prospectively recognizing RA patients at high risk.