Cutaneous dermatomyositis disease course followed over time using the Cutaneous Dermatomyositis Disease Area and Severity Index.

BACKGROUND: Limited studies describe the longitudinal course of cutaneous dermatomyositis (DM). OBJECTIVE: To characterize disease course in treated cutaneous DM by using the Cutaneous Dermatomyositis Disease Area and Severity Index (CDASI), a validated outcome instrument. METHODS: A retrospective cohort included patients with DM who had their CDASI activity subscore recorded for at least 2 years. Disease progression was classified as improved, worsened, or stable, and disease course was classified as monophasic, polyphasic, or chronic. Subjects were divided into groups with disease of mild (n = 16) and moderate-to-severe (n = 24) baseline severity. RESULTS: A total of 40 patients with DM met inclusion criteria. The majority demonstrated improvement in disease activity (n = 21 [52.5%]) rather than worsening (n = 7 [17.5%]) and stable (n = 12 [30.0%]) disease. Most patients with mild disease remained stable (n = 10 [62.5%]), whereas most with moderate-to-severe disease improved (n = 19 [79.2%]). A polyphasic course (n = 33 [82.5%]) predominated over monophasic (n = 5 [12.5%]) and chronic (n = 2 [5%]) courses. The average number of flares per year per number of years of follow-up was independent of baseline disease activity. LIMITATIONS: The retrospective design, potential referral bias, and cutoff values in classification criteria are limitations. CONCLUSION: Baseline CDASI activity score is associated with particular patterns of disease course and progression in cutaneous DM.

Immunological biomarkers in dermatomyositis.

Dermatomyositis (DM) is a chronic acquired disorder that affects primarily the muscle and skin. The pathogenesis of DM, as well as methods for monitoring disease activity and predicting response to therapy, are subjects of active research. Studies looking to unveil the pathogenesis of DM have revealed key molecules that are potential biomarkers of disease activity. This article reviews briefly the recently discovered molecules that are candidate immunological biomarkers for diagnosing and monitoring disease activity in DM.

Early detection of melanoma: reviewing the ABCDEs.

Over the course of their nearly 30-year history, the ABCD(E) criteria have been used globally in medical education and in the lay press to provide simple parameters for assessment of pigmented lesions that need to be further evaluated by a dermatologist. In this article, the efficacy and limitations of the ABCDE criteria as both a clinical tool and a public message will be reviewed.

Biologic predictors of clinical improvement in rituximab-treated refractory myositis.

BACKGROUND: To examine the longitudinal utility of a biomarker signature in conjunction with myositis autoantibodies (autoAbs) as predictors of disease improvement in refractory myositis patients treated with rituximab. METHODS: In the RIM Trial, all subjects received rituximab on 2 consecutive weeks. Using start of treatment as baseline, serum samples (n = 177) were analyzed at baseline and after rituximab with multiplexed sandwich immunoassays to quantify type-1 IFN-regulated and other pro-inflammatory chemokines and cytokines. Biomarker scores were generated for the following pathways: type-1 IFN-inducible (IFNCK), innate, Th1, Th2, Th17 and regulatory cytokines. Myositis autoAbs (anti-synthetase n = 28, TIF-γ n = 19, Mi-2 n = 25, SRP n = 21, MJ n = 18, non-MAA n = 24, unidentified autoantibody n = 9, and no autoantibodies n = 33) determined by immunoprecipitation at baseline, were correlated with outcome measures. Kruskal-Wallis rank sum tests were used for comparisons. RESULTS: The mean (SD) values for muscle disease and physician global disease activity VAS scores (0-100 mm) were 46 (22) and 49 (19). IFNCK scores (median values) were higher at baseline in subjects with anti-synthetase (43), TIF1-γ (31) and Mi-2 (30) compared with other autoAb groups (p < 0.001). At 16 weeks after rituximab, anti-synthetase and Mi-2 autoAb positive subjects and non-MAA had a greater improvement in IFNCK scores (- 6.7, - 6.1 and -7.2, p < .001). Both IFNCK high scores (>30) and autoAb group (Mi-2, non-MAA, and undefined autoantibody) demonstrated the greatest clinical improvement based on muscle VAS (muscle-interaction p = 0.075). CONCLUSION: Biomarker signatures in conjunction with autoAbs help predict response to rituximab in refractory myositis. Biomarker and clinical responses are greatest at 16 weeks after rituximab.

A Clinically and Biologically Based Subclassification of the Idiopathic Inflammatory Myopathies Using Machine Learning.

OBJECTIVE: Published predictive models of disease outcomes in idiopathic inflammatory myopathies (IIMs) are sparse and of limited accuracy due to disease heterogeneity. Computational methods may address this heterogeneity by partitioning patients based on clinical and biological phenotype. METHODS: To identify new patient groups, we applied similarity network fusion (SNF) to clinical and biological data from 168 patients with myositis (64 adult polymyositis [PM], 65 adult dermatomyositis [DM], and 39 juvenile DM [JDM]) in the Rituximab in Myositis trial. We generated a sparse proof-of-concept bedside classifier using multinomial regression and identified characteristics that distinguished these groups. We conducted χ2 tests to link new patient groups with the myositis subtypes. RESULTS: SNF identified five patient groups in the discovery cohort that subdivided the myositis subtypes. The sparse multinomial regressor to predict patient group assignments (areas under the receiver operating characteristic curve = [0.78, 0.97]; areas under the precision-recall curve = [0.55, 0.96]) found that autoantibody enrichment defined four of these groups: anti-Mi-2, anti-signal recognition peptide (SRP), anti-nuclear matrix protein 2 (NXP2), and anti-synthetase (Syn). Depletion of immunoglobulin M (IgM) defined the fifth group. Each group was associated with one subtype, with adult DM being associated with anti-Mi-2 and anti-Syn autoantibodies, JDM being associated with anti-NXP2 autoantibodies, and adult PM being associated with IgM depletion and anti-SRP autoantibodies. These associations enabled us to further resolve the current myositis subtypes. CONCLUSION: Using unsupervised machine learning, we identified clinically and biologically homogeneous groups of patients with IIMs, forming the basis of an integrated disease classification based on both clinical and biological phenotype, thus validating other approaches and what has been previously described.

Clinical Features, Etiologic Factors, Associated Disorders, and Treatment of Palmoplantar Pustulosis: The Mayo Clinic Experience, 1996-2013.

OBJECTIVE: To further characterize clinical characteristics, etiologic factors, associated disorders, and treatment of palmoplantar pustulosis (PPP). PATIENTS AND METHODS: We conducted a retrospective review of patients with PPP at Mayo Clinic between January 1, 1996, and December 31, 2013. RESULTS: Of 215 patients with PPP identified, 179 (83%) were female, and the mean age at onset was 45.3 years. Most patients (n=165, 77%) were current or former smokers. At diagnosis, 15 patients (7%) had an anxiety diagnosis and 9 (4%) had an infection. Nineteen cases (9%) were drug induced. Comorbid conditions included thyroid disease in 18 patients (8%), gluten sensitivity in 3 (1%), and type 2 diabetes mellitus in 21 (10%). In all, 194 patients (90%) received topical corticosteroids, 55 (26%) received phototherapy, and 54 (25%) received systemic agents. CONCLUSION: More than three-fourths of the patients in this study had a history of smoking, which is considered a triggering or aggravating factor for PPP. Regarding comorbid conditions, gluten sensitivity and thyroid disease were found less frequently than previously reported in the literature. Treatment regimens and responses in this cohort varied considerably.

Cancer risk in dermatomyositis: a meta-analysis of cohort studies.

BACKGROUND: An association between dermatomyositis (DM) and cancer has been reported since 1916; however, estimates of the associated risk vary widely. For cost-effectiveness reasons it might be important to elucidate the degree of overall cancer risk in DM. OBJECTIVE: The aim of this systematic review was to investigate the association of cancer in DM by performing a meta-analysis of cohort studies. DATA SOURCES: A systematic literature search of PubMed, Ovid MEDLINE, EMBASE, Web of Science, Scopus, and the Cochrane Collaboration was conducted without language restriction, to 1 May 2014. STUDY SELECTION: Inclusion criteria included cohort studies assessing overall cancer risk in DM. Two reviewers independently performed the study selection. Inter-rater reliability for inclusion decisions was quantified using Cohen's κ statistic. Disagreements were resolved by discussion. DATA EXTRACTION AND SYNTHESIS: Desired variables were extracted from eligible studies independently by two investigators and disagreements were resolved by discussion. Quality of the selected studies was assessed using a modification of a recently employed system designed with reference to Meta-analysis Of Observational Studies in Epidemiology (MOOSE), Quality Assessment Tool for Systematic Reviews of Observational Studies (QATSO), and Strengthening the Reporting of Observational Studies in Epidemiology (STROBE). Summary estimates were derived using a random-effects model. MAIN OUTCOME(S) AND MEASURE(S): Main outcome was the calculated relative risk of developing cancer after diagnosis of DM compared with the general population, estimated as the age- and sex-adjusted standardized incidence ratio (SIR). We hypothesized a priori that the relative risk would be higher in patients diagnosed with DM. RESULTS: A total of 1,272 articles were initially identified but only ten studies met the inclusion criteria. Selected studies included seven population-based and three hospital-based DM cohorts that ranged from 49 to 1,012 patients and had mean follow-up times from 3.7 to 10.4 years. The pooled SIR for the incidence of overall cancer in DM patients was 4.79 (95% confidence interval 3.71-5.87) with significant heterogeneity (I(2) = 85.8%). However, the heterogeneity had no substantial influence on the pooled SIR for overall cancer in DM according to the sensitivity analysis. CONCLUSIONS: Compared with the general population, DM patients are at a significantly increased risk for developing cancer. Understanding the magnitude of this risk is highly relevant toward assisting healthcare providers in clinical decision making, such as screening DM patients for cancer.

Adipokine gene expression in peripheral blood of adult and juvenile dermatomyositis patients and their relation to clinical parameters and disease activity measures.

OBJECTIVE: Recently adipokines have been implicated in the regulation of immune and inflammatory responses in autoimmune disease. To investigate the role of adipokines in adult and pediatric patients with newly diagnosed dermatomyositis (DM), we analyzed peripheral blood and skeletal muscle gene expression of four adipokines: visfatin, leptin, adiponectin and resistin. METHODS: Peripheral blood mononuclear cells (PBMCs) were collected for 21 adult DM, 26 juvenile DM, 5 non-disease adult controls, and 6 non-disease pediatric controls at two time points: baseline and 6 months. Muscle biopsies from 5 adult DM patients and 5 non-disease adult controls were collected at baseline. Similarly, muscle biopsies from 7 juvenile DM patients and 5 non-disease pediatric controls were collected at baseline. The gene expression levels of leptin, adiponectin, resistin, visfatin and related inflammatory cytokines, IL-6, TNF- α, and housekeeping genes GAPDH, B2M, and ACTB were generated using a custom RT(2) Profiler PCR Array. RESULTS: Visfatin gene expression levels in peripheral blood were significantly higher in newly diagnosed adult DM cases compared to non-disease controls (P = 0.004) and these levels correlated with baseline clinical parameters such as age (r = 0.34, P = 0.020), male sex (r = -0.35, P = 0.017), prednisone use (r = -0.42, P = 0.006), and DMARD use (r = 0.35, P = 0.025). No significant association was found between change in visfatin gene expression levels and change in disease activity measures. While visfatin gene expression was significantly up-regulated in muscle tissue of juvenile DM patients (P = 0.028), in adult DM patients only a trend towards significance was observed (P = 0.08). Also, muscle gene expression levels of resistin were significantly elevated in both adult and juvenile DM patients compared respectively to non-disease adult and pediatric controls. Furthermore, an association between peripheral blood resistin gene expression and DM disease activity, including global, muscle, and extra-skeletal disease activity was also observed. CONCLUSION: Peripheral blood visfatin gene expression and muscle resistin gene expression are significantly increased in newly diagnosed adult DM patients. Further longitudinal studies should explore the possibility of using gene expression levels of adipokines such as visfatin and resistin as novel clinical diagnostic biomarkers in DM.