Dataset Information

Association of Fibrosing Myopathy in Systemic Sclerosis and Higher Mortality.

ABSTRACT: OBJECTIVE:To determine if a unique subtype of scleroderma muscle disease exists by comparing the clinical features of systemic sclerosis (SSc; scleroderma) patients with predominant fibrosis on muscle biopsy to those with inflammatory muscle histopathology. METHODS:This retrospective, cross-sectional study included SSc patients with muscle weakness and an available muscle biopsy. Biopsies with fibrosis but without inflammation/necrosis were designated as "fibrosing myopathy," and those with inflammation and/or necrosis were assigned a category of "inflammatory myopathy." Clinical data, including features of SSc, serum creatine kinase (CK) levels, electromyography, autoantibody profile, and survival, were compared between the 2 groups. RESULTS:The study population consisted of 37 weak SSc patients, 8 with fibrosing myopathy and 29 with inflammatory myopathy. Compared to those with inflammatory myopathy, patients with fibrosing myopathy were more likely to have diffuse SSc skin subtype (87% versus 62%; P = 0.18), African American race (62.5% versus 37.9%; P = 0.20), and a lower mean ± SD forced vital capacity (55.5 ± 31.9 versus 66.4 ± 17.6; P = 0.23). They also had lower mean ± SD CK values (516 ± 391 versus 2,477 ± 3,511 IU/liter; P = 0.007) and lower aldolase values (13.8 ± 4.7 versus 27.3 ± 4.7; P = 0.01). Patients with fibrosing myopathy had a significantly higher mortality (5 of 8 [62.5%] versus 4 of 29 [14.3%]; P = 0.005). CONCLUSION:Fibrosing myopathy is a unique histologic subtype of muscle disease among weak patients with SSc and is associated with significantly worse mortality compared to those with inflammation and/or necrosis on muscle biopsy.

SUBMITTER: Paik JJ

PROVIDER: S-EPMC5791890 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Association of Fibrosing Myopathy in Systemic Sclerosis and Higher Mortality.

Paik Julie J JJ Wigley Fredrick M FM Shah Ami A AA Corse Andrea M AM Casciola-Rosen Livia L Hummers Laura K LK Mammen Andrew L AL

Arthritis care & research 20171101 11

<h4>Objective</h4>To determine if a unique subtype of scleroderma muscle disease exists by comparing the clinical features of systemic sclerosis (SSc; scleroderma) patients with predominant fibrosis on muscle biopsy to those with inflammatory muscle histopathology.<h4>Methods</h4>This retrospective, cross-sectional study included SSc patients with muscle weakness and an available muscle biopsy. Biopsies with fibrosis but without inflammation/necrosis were designated as "fibrosing myopathy," and ...[more]

PMID: 28544788

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Project description:OBJECTIVE:The objective of this study is to evaluate racial/ethnic differences in disease manifestations and survival in a US cohort of patients with systemic sclerosis (SSc), with a focus on Asian patients. METHODS:A retrospective cohort study was conducted among Kaiser Permanente Northern California adults with an incident SSc diagnosis by a rheumatologist from 2007 to 2016, confirmed by a chart review to fulfill 2013 American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) classification criteria. Self-reported race/ethnicity was categorized as non-Hispanic white, Asian, Hispanic, and black. Disease manifestations and survival were compared, using white patients as the reference. RESULTS:A total of 609 patients with incident SSc were identified: 89% were women, and 81% had limited cutaneous SSc, with a mean age at diagnosis of 55.4 ± 14.8 years. The racial/ethnic distribution was 51% non-Hispanic white (n = 310), 25% Hispanic (n = 154), 16% Asian (n = 96), and 8% black (n = 49). Compared with white patients, black patients had a greater prevalence of diffuse disease (14.5% vs. 44.9%; P < 0.001), and Asians had higher rates of anti-U1-RNP antibodies (32.1% vs. 11.9%; P = 0.005). Nine-year overall survival rates following SSc diagnosis were lower in Asian (52.3%), black (52.2%), and Hispanic patients (68.2%) compared with white patients (75.8%). Pulmonary hypertension and infections were the leading causes of death in Asian patients. Asian race was associated with higher mortality on univariable (hazard ratio [HR] 1.83 [95% confidence interval (CI) 1.08-2.99]; P = 0.020) and multivariable analyses (HR 1.80 [95% CI 0.99-3.16]; P = 0.047) when adjusting for age, sex, body mass index, cutaneous subtype, smoking status, interstitial lung disease, pulmonary hypertension, renal crisis, and malabsorption syndrome. CONCLUSION:Asian patients with SSc in this US cohort had increased mortality compared with white patients. These patients warrant close monitoring for disease progression.

Project description:Clinical predictors of mortality in systemic sclerosis (SSc) are diversely reported due to different healthcare conditions and populations. A simple predictive model for early mortality among patients with SSc is needed as a precise referral tool for general practitioners. We aimed to develop and validate a simple predictive model for predicting mortality among patients with SSc. Prognostic research with a historical cohort study design was conducted between January 1, 2013, and December 31, 2020, in adult SSc patients attending the Scleroderma Clinic at a university hospital in Thailand. The data were extracted from the Scleroderma Registry Database. Early mortality was defined as dying within 5 years after the onset of SSc. Deep learning algorithms with Adam optimizer and different machine learning algorithms (including Logistic Regression, Decision tree, AdaBoost, Random Forest, Gradient Boosting, XGBoost, and Autoencoder neural network) were used to classify SSc mortality. In addition, the model's performance was evaluated using the area under the receiver operating characteristic curve (auROC) and its 95% confidence interval (CI) and values in the confusion matrix. The predictive model development included 528 SSc patients, 343 (65.0%) were females and 374 (70.8%) had dcSSc. Ninety-five died within 5 years after disease onset. The final 2 models with the highest predictive performance comprise the modified Rodnan skin score (mRSS) and the WHO-FC ≥ II for Model 1 and mRSS and WHO-FC ≥ III for Model 2. Model 1 provided the highest predictive performance, followed by Model 2. After internal validation, the accuracy and auROC were good. The specificity was high in Models 1 and 2 (84.8%, 89.8%, and 98.8% in model 1 vs. 84.8%, 85.6%, and 98.8% in model 2). This simplified machine learning model for predicting early mortality among patients with SSc could guide early referrals to specialists and help rheumatologists with close monitoring and management planning. External validation across multi-SSc clinics should be considered for further study.

Dataset Information

Association of Fibrosing Myopathy in Systemic Sclerosis and Higher Mortality.

Publications

Association of Fibrosing Myopathy in Systemic Sclerosis and Higher Mortality.

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