New tool may accurately predict risk of death for AAV patients
Nomogram based on 16 factors predicted survival in single-center study

A graphic prediction tool may accurately estimate the chance of survival over two years in people ANCA-associated vasculitis (AAV), according to a study at a single Chinese hospital.
The tool, a nomogram based on 16 predictive factors, was able to differentiate patients who survived from those who didn’t with an accuracy of 82.5%, researchers said.
While it has yet to be validated for use in larger and more diverse patient populations, the nomogram showed “good performance” and “is expected to provide a scientific basis for the management and treatment of AAV,” the researchers wrote.
The study, “Comprehensive characteristics of pulmonary antineutrophil cytoplasmic antibody-associated vasculitis and the development of a predictive nomogram for mortality,” was published in International Immunopharmacology.
AAV is an autoimmune disease that causes inflammation and damage to small blood vessels, most commonly in the lungs and kidneys. Lung involvement is “a significant contributor to mortality,” the researchers wrote, adding it can cause bleeding into the air sacs, known as diffuse alveolar hemorrhage (DAH), which can progress to respiratory failure and death.
Risk of death for AAV patients
While lung problems can increase the risk of death, it can be difficult to distinguish AAV from lung infections when the disease is in its early stages, leading to misdiagnosis, “delayed intervention and suboptimal treatment,” the researchers wrote.
Several predictive models of mortality have been developed, but these “are often constrained by smaller sample sizes and limited applicability to specific subgroups, underscoring the need for more robust and generalized models that address the broader AAV population,” the researchers wrote.
The team set out to compare the features of AAV patients with and without lung involvement, and develop a new predictive tool of death for all AAV patients.
They retrospectively reviewed the medical records of 538 people admitted to West China Hospital from January 2013 to July 2019 and diagnosed with AAV. Patients were followed until August 2020, or until the occurrence of certain predefined outcome measures.
The 460 patients (85.5%) who had lung involvement were significantly older than those without lung involvement (64 vs. 56). They were also significantly more likely to be men (51.7% vs. 34.6%), to smoke (38.3% vs. 20.5%), and to have multi-organ involvement (60.2% vs. 25.6%).
Patients with lung involvement also had significantly more severe disease, stayed in the hospital for longer periods, and faced higher medical costs than those without lung involvement.
The lung involvement group was also significantly more likely to have weight loss, symptoms of nerve damage outside the brain and spinal cord, cough, thick lung mucus production, blood in cough, shortness of breath, and fever, but less likely to have excess protein in the urine (a sign of kidney damage).
DAH was present in 23% of patients with lung involvement and in none of those without. Lung involvement was also significantly associated with a higher likelihood of experiencing respiratory failure and requiring mechanical ventilation.
A significantly greater proportion of patients with lung involvement died during the study (38.7% vs. 25.6%).
The findings indicate that “lung involvement is frequent in AAV patients and with higher rates of mortality,” the team wrote.
The researchers then compared data from AAV patients who survived versus those who didn’t in order to identify potential risk factors of death. They found that nonsurviving patients were generally older and had higher disease severity and were more likely to have greater involvement of the kidneys, lungs, and multiple organs.
Further statistical analyses identified 16 potential risk factors to be included in the nomogram designed to predict mortality among people with AAV. These factors included age, admission into the intensive care unit, long-term use of corticosteroids, use of antibiotics, DAH, respiratory failure, acute kidney injury, blood cell counts, disease relapse, infection, and disease severity.
The new tool was able to predict patients’ mortality with 82.5% accuracy, demonstrating an “excellent agreement between the predicted and observed 1-year, 2-year survival outcomes,” the researchers wrote.
All patients with risk scores higher than the median value and classified as being at high risk of death died during follow-up.
“The study establishes a predictive model for AAV mortality with high accuracy, offering insights crucial for patient care,” the researchers wrote.