Disease-Related Factors Predict Risk for CV Events in ANCA-Associated Vasculitis

In antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV), risk factors for cardiovascular (CV) events included age, diabetes, and a history of CV events, according to the results of a study published in Joint Bone Spine.

The Cardiovascular Risk in ANCA-associated Vasculitis (CVD-AAV) study was a prospective cohort study conducted at 2 centers in Canada and the Netherlands between 2016 and 2018 to evaluate disease-specific CV risk determinants and outcomes in AAV.

Patients with AAV were followed-up every year until the first CV event up to 5 years. Predictors for CV events were evaluated. Uncontrolled diabetes was defined as glycated hemoglobin (HbA1_C) of at least 53 mmol/mol (≥7%).

A total of 144 patients with AAV were included in the study, with a mean age of 62 (SD, 15) years; 44% were women. Overall, 69% had granulomatosis with polyangiitis (GPA) subtype disease, 58% had proteinase 3 (PR3) subtype at diagnosis and had been diagnosed 5.1 (SD, 8.4) years previously.

A CV event occurred among 11% of patients at a median of 2.90 years, 2 of which were fatal. The incidence rate of CV events was 5.45 per 100 patient-years (py) among all patients and 3.39 per 100 py among those with a history of CV events.

In the univariate analysis, age, systolic blood pressure, diabetes, HbA1_C, CV history, and Framingham risk score were predictors for CV events.

In the age-adjusted analysis, uncontrolled diabetes (adjusted hazard ratio [aHR], 4.42; 95% CI, 1.30-14.9; P <.05), diabetes (aHR, 2.94; 95% CI, 1.03-8.39; P <.05), CV event history (aHR, 2.86; 95% CI, 1.06-7.68; P <.05), and HbA1_C per mmol/mol increase (HR, 1.05; 95% CI, 1.01-1.09; P <.01) remained significant predictors for CV events.

Study limitations included survival bias, as patients were enrolled many years after diagnosis.

These data indicated that age and disease-related factors predicted CV event risk in AAV. The study authors concluded, “Ultimately, to identify high-risk patients, ANCA-specific CV risk prediction models should be developed and validated in large international cohorts. Treatment of CV risk factors is essential to optimize long-term outcomes in patients with AAV.”