Long-Term Prognostic Factors in Patients With Antineutrophil Cytoplasmic Antibody-Associated Vasculitis: A 15-Year

Qian-Qian Liao1, Ya-Fei Ren2, Ke-Wei Zhu3,4

  • 1Department of Pharmacy, People's Hospital of Guilin, Guilin, China.

Abstract

Insights

This study identified key predictors of long-term survival in antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) patients. Laboratory test results at diagnosis are crucial for predicting survival outcomes in AAV.

Area of Science:

  • Rheumatology
  • Immunology
  • Internal Medicine

Background:

  • Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a multisystem autoimmune disease affecting small vessels.
  • Microscopic polyangiitis (MPA) and granulomatosis with polyangiitis (GPA) are primary clinicopathologic variants of AAV.
  • Myeloperoxidase (MPO) and proteinase 3 (PR3) are key target antigens in AAV pathogenesis.

Purpose of the Study:

  • To investigate predictive factors for long-term survival in patients diagnosed with AAV.
  • To develop a predictive model for estimating survival rates in AAV patients.

Main Methods:

  • A multicenter retrospective study involving 407 AAV patients from 2005 to 2020.
  • Collected clinical and laboratory data including ANCA types, autoantibodies (ANA, ENA), GFR, and inflammatory markers.
  • Utilized survival analysis and constructed a nomogram to predict 3-year and 5-year survival rates.

Main Results:

  • The study analyzed 407 patients, with MPA and GPA being the most common variants (82.6% and 11.3%, respectively).
  • Identified independent prognostic factors for overall survival: age, pathological type, ANCA status (MPO/PR3), ANA, GFR, lymphocyte count, NLR, and CRP.
  • The developed nomogram demonstrated good predictive accuracy for 3-year and 5-year survival rates (C-index: 0.721).

Conclusions:

  • Laboratory test results obtained at the time of diagnosis are highly significant for predicting long-term survival in AAV patients.
  • The established nomogram provides a practical and accurate tool for predicting survival in AAV, aiding clinical decision-making.

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