Park, Tricia

Objective To examine real‐world patterns in pain management among adults with systemic lupus erythematosus (SLE), we focused on the sequencing of pain modalities, polypharmacy, and demographic variation. Methods We conducted a retrospective analysis of electronic health records from adults with SLE treated at a single academic medical center between 2005 and 2024. We included patients who received at least one pain‐related therapy, including glucocorticoids, opioids, nonsteroidal anti‐inflammatory drugs (NSAIDs), antidepressants, anticonvulsants, muscle relaxants, and nonpharmacologic interventions. We used sequence analysis and Sankey diagrams to map treatment trajectories and compared patterns across two periods: 2005 to 2014 and 2015 to 2024. Polypharmacy was defined as receiving five or more pain‐related prescriptions within 12 months. We examined trends by age, sex, and race or ethnicity. Results Among 769 patients, initiation of glucocorticoids and opioids declined over time (58%–51% and 28%–22%, respectively), whereas NSAID use increased (19%–29%). The median number of pain prescriptions decreased, and polypharmacy prevalence dropped from 53% to 45%. In recent years, younger adults and men received more prescriptions, with 69% of men receiving five or more compared with 43% of women. Racial disparities narrowed overall in recent years but persisted in sensitivity analyses excluding glucocorticoids. Conclusion Pain management in SLE is shifting away from high‐risk therapies; however, prescribing intensity remains high and varies by demographic group. Visualizations serve as a complementary lens to traditional prescription counts, allowing representation of polypharmacy not only by volume but also by the diversity and sequencing of therapeutic classes over time.

Objective Patients with chronic illness share their experiences in online communities and generate rich data on pain management. This study applied natural language processing methods, including large language models (LLMs), to Reddit discussions from lupus communities to characterize multidimensional pain experiences framed in the biopsychosocial model. Methods We extracted Reddit posts from the r/Lupus and r/LupusSupport subreddits posted from June 9, 2010, through December 31, 2023. Pain‐related posts were identified using a clinically informed pain lexicon. Topic modeling was used to identify thematic patterns, which were then compared with structured summaries generated by LLM instructions that were fine‐tuned using the biopsychosocial model of pain. Two reviewers conducted content analysis of the LLM‐generated summaries, evaluating thematic accuracy and coverage. Results Data from Reddit included 31,785 posts from 10,857 authors. We identified common pain complaints, management strategies, and sociocultural, affective, and nociplastic dimensions of pain. Instruction fine‐tuned LLMs produced structured summaries with an average thematic accuracy score of 3.1 of 4 (kappa = .09) and content coverage score of 2.9 of 4 (kappa = .38). Sociocultural features presented in 123 posts (33.8%), including peer support and validation (n = 106) and provider interactions or access issues (n = 35). Nociplastic pain presented in 205 posts (56.3%). Conclusion Natural language processing methods can be used to extract rich, multidimensional insights into pain experiences from online communities focused on lupus. These approaches highlight the psychological, social, and cultural facets of pain that may be underrepresented in clinical settings, supporting more patient‐centered approaches to care in rheumatology.

Chronic pain is a pervasive and complex symptom experienced by patients with Systemic Lupus Erythematosus (SLE), often impacting their quality of life. Traditional data sources, such as clinical records and surveys, provide valuable insights but may not fully capture the breadth of patient experiences and self-management strategies. This study leverages Reddit discussions as a real-world data source to explore chronic pain patterns, management approaches, and unmet needs among individuals with SLE. Utilizing natural language processing (NLP), we analyzed over 30,000 posts from r/Lupus and r/LupusSupport subreddits to identify key themes, trends, and alternative therapies discussed by users. This approach highlights the potential of social media as a complementary resource for understanding chronic pain and guiding patient-centered care interventions.