Predicting relapse in ANCA-associated vasculitis: a systematic review and meta-analysis

King, C., Druce, K. L., Nightingale, P., Kay, E., Basu, N. , Salama, A. D. and Harper, L. (2021) Predicting relapse in ANCA-associated vasculitis: a systematic review and meta-analysis. Rheumatology Advances in Practice, 5(3), rkab018. (doi: 10.1093/rap/rkab018) (PMID:34476335) (PMCID:PMC8407598)

[img] Text
236134.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial.

381kB

Abstract

Objectives: Relapses affect 30-50% of patients with anti-neutrophil cytoplasm antibody (ANCA) associated vasculitis (AAV) over 5 years, necessitating long term treatment. Whilst there have been studies looking at predictors of relapse in AAV, this research has yet to translate clinically into guidance on tailored therapy. The aim of this systematic review was to identify and meta-analyse existing risk factors from the literature and produce a model to calculate individualised patient relapse risk. Method: A search strategy was developed to include all studies identifying predictors of AAV relapse using multivariate analysis. Individual risk factors were extracted, and pooled hazard ratios (HRs) calculated. A model to predict time to first relapse based on identified risk factors was retrospectively tested using a cohort of patients with AAV. Results: The review of 2,674 abstracts identified 117 papers for full text review, with 16 eligible for inclusion. Pooled HRs were calculated from significant risk factors including PR3 ANCA positivity HR 1.69 (1.46-1.94), cardiovascular involvement HR 1.78 (1.26-2.53), creatinine >200µmol/l (relative to creatinine ≤100) HR 0.39 (0.22-0.69) and creatinine 101-200µmol/l HR 0.81 (0.77-0.85). Using data from 182 AAV patients to validate the model gave a C-statistic of 0.61. Conclusion: PR3 ANCA positivity, lower serum creatinine and cardiovascular system involvement are all associated with an increased risk of relapse and a combination of these risk factors can be used to predict an individual’s relapse risk. In order to produce a clinically useful model to stratify risk, we need to identify more risk factors with a focus towards robust biomarkers.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Basu, Professor Neil
Authors: King, C., Druce, K. L., Nightingale, P., Kay, E., Basu, N., Salama, A. D., and Harper, L.
College/School:College of Medical Veterinary and Life Sciences > Institute of Infection Immunity and Inflammation
Journal Name:Rheumatology Advances in Practice
Publisher:Oxford University Press
ISSN:2514-1775
ISSN (Online):2514-1775
Published Online:09 March 2021
Copyright Holders:Copyright © 2021 The Authors
First Published:First published in Rheumatology Advances in Practice 5(3): rkab018
Publisher Policy:Reproduced under a Creative Commons License

University Staff: Request a correction | Enlighten Editors: Update this record