The “Clinical Topics” from the Electronic Health Record of Patients with Rheumatoid Arthritis Before Initiating Targeted Therapies and Association with Future Treatment Course
Year: 2025
Type: article
Study design: Observational Study
Abstract: OBJECTIVE: Rheumatoid arthritis (RA) is a heterogeneous disease, with patients experiencing varied disease courses and responses to treatment. The objective of this study was to apply topic modeling to RA patient electronic health record (EHR) data and determine (1) the clinical topics/subgroups in those with RA before initiation of a biologic/targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD) and (2) whether the clinical topics were associated with subsequent RA treatment course. METHODS: We studied patients from a validated EHR-based RA cohort who initiated a b/tsDMARD between 2011 and 2019. Diagnoses codes, laboratory data, and medication prescriptions in the year before their first b/tsDMARD initiation were extracted. Latent Dirichlet allocation, a topic modeling method, was applied to define the underlying "topics" representing clinical subgroups. We used multinomial regression to test association between the clinical topic with four previously published treatment trajectories: tumor necrosis factor inhibitor (TNFi) persisters, TNFi to abatacept, and those prescribed multiple b/tsDMARDs enriched with tocilizumab or rituximab. RESULTS: From the data of 1,102 patients with RA, diagnoses codes, laboratory data, and prescriptions from the year before b/tsDMARD initiation resulted in four main clinical topics/subgroups: (A) RA codes/methotrexate (MTX), (B) arthralgia/osteoarthritis, (C) hypertension (HTN)/cardiovascular (CV) comorbidities, and (D) mood disorders. Those with RA codes/MTX topic were more likely to persist on TNFi. Conversely, those associated with the HTN/CV topic were more likely to cycle through multiple b/tsDMARDs. CONCLUSION: Clinical topics derived from the EHR data of patients with RA before b/tsDMARD differentiated future RA treatment course. HTN/CV comorbidities were associated with a future need for multiple b/tsDMARD therapies.
Source: ACR Open Rheumatology
DOI: 10.1002/acr2.70118
Language: English
Subfield: Rheumatology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,550
Awards: G1583876762, Bridging clinical trial and real-world data via machine learning to advance rheumatoid arthritis treatment strategies, Mentoring Patient-Oriented Research Leveraging Bioinformatics to Study CV Risk in Rheumatic Disease, VERITY: Value and Evidence in Rheumatology using bioInformaTics, and advanced analYtics
OpenAlex ID: W4416933629
