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Abstract Number: 0292

Patterns and Predictors of Longitudinal Trajectories of Pain in Individuals with Inflammatory Myopathies

Haley Zimmerman1, Ethan Ritz2, Kristin Wipfler3, Kaleb Michaud4 and Didem Saygin1, 1Rush University Medical Center, Chicago, IL, 2Rush Research Informatics Core, Rush University Medical Center, Chicago, IL, 3FORWARD, The National Databank for Rheumatic Diseases, Omaha, NE, 4University of Nebraska Medical Center, Omaha, NE

Meeting: ACR Convergence 2025

Keywords: Myopathies, Myositis, pain

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Session Information

Date: Sunday, October 26, 2025

Title: (0280–0305) Muscle Biology, Myositis & Myopathies – Basic & Clinical Science Poster I

Session Type: Poster Session A

Session Time: 10:30AM-12:30PM

Background/Purpose: Idiopathic inflammatory myopathies (IIM) have historically been considered a disease of painless weakness. However, recent studies indicate that most patients with IIM experience pain that interferes with their daily activities. Despite the high prevalence and burden of pain, longitudinal pain trajectories of patients with IIM are currently unknown. Understanding the temporal course of pain in these patients can inform clinicians about risk stratification and assist with long-term pain management. In this study, we aimed to explore longitudinal changes in pain levels and to examine the relationship between changes in pain and various clinical variables in individuals with IIM.

Methods: The FORWARD Databank is a longitudinal prospective registry of adults in the US with rheumatic diseases. The Databank includes patient-reported biannual forms related to their socio-demographics, disease activity and subtypes, comorbidities, symptoms including pain levels (21-point numeric rating scale), and medications. We identified participants with IIM diagnosis in FORWARD who had pain scores at ≥2 time points. Pain trajectories over time were fit using latent class mixed models with the lcmm package in R version 4.4.3. Pain was modeled as an ordinal outcome, using the “thresholds” link function. The model included a fixed effect for time and included random intercepts and slopes for each participant. Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were used to determine the optimal number of latent classes. We compared the baseline characteristics of the two groups with chi square test and t test/Fisher’s exact test where appropriate. To further examine the factors associated with change in pain levels over time, univariate and multivariable linear mixed models were performed.

Results: A total of 147 individuals with IIM (mean age of 54.6 [±13.8], female 78.9%) were included in the study. Two groups were identified: improving (57%; n=84) and stable longitudinal pain trajectories (43%; n=63) (Figure 1). Pain levels of the improving group started at 4.31 and improved by 0.14 per year. The pain trajectories were in line with longitudinal change in patient global disease activity. The participants with improving pain trajectory had worse baseline pain levels, patient global disease activity, fatigue and disability, and more commonly reported joint swelling, rash, photosensitivity, and muscle weakness than those in stable group (Table 1). Baseline demographics, disease subgroups, socioeconomic variables, and comorbidities, including osteoarthritis and fibromyalgia, were generally comparable between the two trajectory groups. Younger age, higher BMI, analgesic use and higher patient global disease activity were significantly associated with increase in pain levels over time in multivariable models (Table 2).

Conclusion: Pain levels improved over time in nearly 60% of the individuals with IIM, while the rest had stable pain levels. Individuals with improving pain trajectory were more likely to have active disease. A close link between pain trajectories and myositis disease activity suggests that pain could be a clinical manifestation of IIM.

Supporting image 1Figure 1. Longitudinal pain trajectories of adults with IIM and the corresponding change in patient global disease activity in each group (Blue line with grey area: LOESS line with confidence interval; Red line: Trajectory line).

Supporting image 2

Supporting image 3


Disclosures: H. Zimmerman: None; E. Ritz: None; K. Wipfler: None; K. Michaud: None; D. Saygin: None.

To cite this abstract in AMA style:

Zimmerman H, Ritz E, Wipfler K, Michaud K, Saygin D. Patterns and Predictors of Longitudinal Trajectories of Pain in Individuals with Inflammatory Myopathies [abstract]. Arthritis Rheumatol. 2025; 77 (suppl 9). https://acrabstracts.org/abstract/patterns-and-predictors-of-longitudinal-trajectories-of-pain-in-individuals-with-inflammatory-myopathies/. Accessed .
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