LONDON — A research group in the United Kingdom conducted an epidemiological study over a 19-year period, revealing patterns in the incidence of idiopathic inflammatory myopathy (IIM) subtypes across different demographic groups. Separately, the CapIAMI group developed a standardized automated nailfold videocapillaroscopy model to predict disease activity in IIM patients.
The study identified 4,105 individuals diagnosed with dermatomyositis, inclusion body myositis, or other IIMs. The crude incidence of all three myopathy subtypes increased during the 19-year study period. However, age-standardized incidence rates remained stable, suggesting that demographic aging, rather than a true increase in disease occurrence, likely influenced the observed pattern.
The research found that female patients exhibited a higher incidence of dermatomyositis and other IIM subtypes compared to male patients. Conversely, male patients had a higher incidence of inclusion body myositis. The recorded incidence of inclusion body myositis was lower in the most deprived areas when compared to the least deprived areas.
Incidence patterns varied by ethnicity. Individuals of South Asian, black, and mixed ethnic groups showed a higher risk of other IIM subtypes than those of white ethnicity. Furthermore, individuals of South Asian, black, and unknown ethnicities displayed a higher incidence of dermatomyositis than individuals of white ethnicity.
Patrick Gordon, a researcher, said, "This is one of the first population-based studies to characterise the epidemiology of IIM subtypes across key sociodemographic groups. Our findings indicate that subtypes differ in incidence - particularly by sex and ethnicity - providing much-needed insight into these conditions across the lifespan and among diverse populations."
Nailfold videocapillaroscopy directly visualizes microvascular inflammation. Researchers developed five predictive models, testing combinations of nailfold videocapillaroscopy, laboratory findings, capillary density, and lactate dehydrogenase values. The model that combined nailfold videocapillaroscopy and laboratory data achieved a sensitivity of 60.2 percent and a specificity of 83.3 percent.
The nailfold videocapillaroscopy-only model outperformed assessments based solely on traditional laboratory data. Multivariable logistic regression identified capillaroscopy parameters as the dominant independent predictors of disease activity, with traditional biomarkers providing minimal independent predictive value. This quantitative capillaroscopy model produced a positive predictive value of 91.4 percent for identifying active disease. Study authors recommended integrating automated microvascular imaging into routine disease monitoring protocols.