Heterogeneous Disease Trajectories Explain Variable Radiographic, Function and Quality of Life Outcomes in the Canadian Early Arthritis Cohort (CATCH)

异质性疾病轨迹解释了加拿大早期关节炎队列(CATCH)中放射学、功能和生活质量结果的差异

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Abstract

Our objective was to identify distinct trajectories of disease activity state (DAS) and assess variation in radiographic progression, function and quality of life over the first two years of early rheumatoid arthritis (ERA). The CATCH (Canadian early ArThritis CoHort) is a prospective study recruiting ERA patients from academic and community rheumatology clinics in Canada. Sequential DAS28 scores were used to identify five mutually exclusive groups in the cohort (n = 1,586) using growth-based trajectory modeling. Distinguishing baseline sociodemographic and disease variables, treatment required, and differences in radiographic progression and quality of life measures over two years were assessed. The trajectory groups are characterized as: Group 1 (20%) initial high DAS improving rapidly to remission (REM); Group 2 (21%) initial moderate DAS improving rapidly to REM; Group 3 (30%) initial moderate DAS improving gradually to low DAS; Group 4 (19%) initial high DAS improving continuously to low DAS; and Group 5 (10%) initial high DAS improving gradually only to moderate DAS. Groups differed significantly in age, sex, race, education, employment, income and presence of comorbidities. Group 5 had persistent steroid requirements and the highest biologic therapy use. Group 2 had lower odds (OR 0.22, 95%CI 0.09 to 0.58) and Group 4 higher odds (OR 1.94, 95%CI 0.90 to 4.20) of radiographic progression compared to Group 1. Group 1 had the best improvement in physical function (Health Assessment Questionnaire 1.08 (SD 0.68) units), Physical Component Score (16.4 (SD 10.2) units), Mental Component Score (9.7 (SD 12.5) units) and fatigue (4.1 (SD 3.3) units). In conclusion, distinct disease activity state trajectories explain variable outcomes in ERA. Early prediction of disease course to tailor therapy and addressing social determinants of health could optimize outcomes.

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