Improved Classification Systems Needed for AAV, Study Shows

Marta Figueiredo, PhD avatar

by Marta Figueiredo, PhD |

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The autoimmune condition ANCA-associated vasculitis (AAV) needs improved classification systems that can better predict disease outcomes, a Spanish study says.

Disease management should be based more on individual patient characteristics and levels of disease severity than on general classifications or ANCA specificities, the researchers suggest.

The study, “The complexity of classifying ANCA-associated small-vessel vasculitis in actual clinical practice: data from a multicenter retrospective survey,” was published in the journal Rheumatology International.

AAV is a group of autoimmune diseases caused by the production of ANCAs — autoantibodies against proteins present in neutrophils, a type of immune cell. That leads to damage to small blood vessels and swelling in affected tissues and organs.

The most common ANCAs target one of two proteins present in healthy neutrophils: proteinase 3 (PR3) and myeloperoxidase (MPO).

The International Chapel Hill Consensus Conference (CHCC) divided AAV into three major types: microscopic polyangiitis (MPA), granulomatosis with polyangiitis (GPA), and eosinophilic granulomatosis with polyangiitis (EGPA). Each is characterized by different symptoms and prognoses, but there are some overlapping features between them.

Patients with GPA produce mainly PR3 antibodies, while those with MPA are mainly positive for MPO antibodies, although ANCA specificity overlaps only partially with these clinical types.

Considering the non-exclusive symptoms or type of ANCA associated with each form of AAV, several sets of criteria for the diagnosis of AAV have been developed over the years. However, some have conflicting criteria. Recent studies also have suggested the combined or single use of ANCA specificities to classify AAV.

There is a general feeling of dissatisfaction with the current diagnostic systems, and their ability to predict relapse, end-stage renal disease (ESRD) — which is, essentially, kidney failure — or survival.

Researchers in Spain sought to evaluate the possible causes of the difficulties physicians found in classifying AAV patients. To do so, they analyzed the clinical data of 115 adults with AAV diagnoses from five Spanish hospitals.

Patients were classified according to CHCC type, European Medicines Agency algorithm, and the five clinical types from the French Vasculitis Study Group and the European Vasculitis Society. They were followed for three years. Median age at diagnosis was 69 years, and 60% (69) of participants were men.

More than half of the patients (64%) showed MPO antibodies, and 23% were positive for PR3 antibodies. Participants with PR3 antibodies had a higher frequency of eye, ear, nose, throat, skin, and lung involvement. Meanwhile, those with MPO antibodies frequently developed peripheral neuropathy, or nerve damage outside the brain and spinal cord.

The results showed that 53 people (46%) did not have any distinctive data of GPA, MPA, or EGPA — not fulfilling any diagnostic criteria — and could be classified under at least two definitions. There also were discrepancies between systems in terms of the distribution of patients into specific AAV categories.

The team concluded that AAV classification is difficult due to three main reasons. First is the lack of specific features to classify patients under the different AAV types. In most cases, clinical data is enough to confirm AAV diagnosis, but insufficient to categorize people under one AAV type.

The second difficulty is the discordance between clinical or tissue data and ANCA specificities. “Neither the presence nor the absence of PR3 or MPO ANCA antibodies is sensitive or specific enough to indicate or exclude any of the major … variants,” the researchers said.

Lastly, the investigators pointed to the lack of agreement and consistency between the different classification systems as another limiting factor for AAV determinations.

As part of their research, the team also tested the usefulness of different variables to predict patients’ relapse, ESRD, and death.

They found that a more severe disease at diagnosis, or lung involvement, was significantly associated with lower survival rates than milder disease or no disease-associated lung damage.

Patients with disease-related eye damage were more likely to have disease relapse than those without it. Those with poor kidney function — assessed by the estimated glomerular filtration rate at diagnosis — were more likely to develop ESRD.

Further, the researchers said, administration of induction and maintenance treatment according to the 2009 European League Against Rheumatism (EULAR) guidelines significantly increased patient survival.

The team concluded that the new data are consistent with previous recommendations stating that “a structured clinical assessment which includes all potentially affected organs and systems and a categorization of disease severity continue to be the best tools to predict prognosis and tailor treatment, independently of the CHCC definitions or AAV [specificities].”

They believe future research should be focused on the development of new diagnostic classification systems for AAV, and the identification of new biomarkers.