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A retrospective natural history study in adult and juvenile patients with incident dermatomyositis and polymyositis using real world data.

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PMID40875130
JournalClinical rheumatology
Publication Date2025-08-28
Ingested2026-08-02 12:05 AM
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ABSTRACT

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OBJECTIVE: This retrospective natural history study used real-world data to describe baseline demographics, comorbidities, clinical characteristics, and treatments, and assess incidence rates (IRs) of extra-muscular outcomes in patients with incident dermatomyositis (DM), polymyositis (PM), juvenile DM (JDM), and juvenile PM (JPM). METHODS: De-identified clinical data were collected from the US Optum® electronic health records with supplemental claims (01 January 2016 to 31 March 2021). Total 9,009 patients were included (DM: 4,275; PM: 4,559; JDM: 128; JPM: 47). IRs of 13 outcomes were estimated in patients and an equal number of sex- and age-matched controls (MCs) without DM/PM. RESULTS: Mean age at index was 54.5 (DM), 57.3 (PM), 14.3 (JDM), and 15.1 years (JPM). Most common comorbidities were hypertension in DM (50.3%) and PM (63.9%) cohorts, dysphagia in JDM (15.6%) and liver disease in JPM (23.4%) cohorts. Most common clinical characteristics were Raynaud's phenomenon in DM (8.6%), PM (7.9%), and JDM (11.7%) cohorts, and arthritis in JPM (10.6%) cohort. Systemic steroids were the most frequent medication (DM: 70.3%; PM: 68.3%; JDM: 73.4%; JPM: 59.6%). IRs (per 100 person years) of outcomes in all cohorts were higher in patients versus their MCs. In DM and PM cohorts, highest IRs were observed for gastroesophageal reflux disease (DM:10.3; PM:12.8). In JDM cohort, dysphagia (4.3) had highest IR. In JPM cohort, cardiac dysrhythmia (3.5) had highest IR. CONCLUSION: This study addresses existing gaps in understanding the descriptive epidemiology of DM and PM in the US, particularly the IRs of extra-muscular disease manifestations and malignancy events.

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A retrospective natural history study in adult and juvenile patients with incident dermatomyositis and polymyositis using real world data.

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