PT  - JOURNAL ARTICLE
AU  - Roland Linder
AU  - Isabelle Orth
AU  - E. Christian Hagen
AU  - Fokko J. van der Woude
AU  - Wilhelm H. Schmitt
TI  - Differentiation Between Wegener's Granulomatosis and Microscopic Polyangiitis by an Artificial Neural Network and by Traditional Methods
AID  - 10.3899/jrheum.100814
DP  - 2011 Feb 15
TA  - The Journal of Rheumatology
PG  - jrheum.100814
4099  - http://www.jrheum.org/content/early/2011/02/14/jrheum.100814.short
4100  - http://www.jrheum.org/content/early/2011/02/14/jrheum.100814.full
AB  - Objective To investigate the operating characteristics of the American College of Rheumatology (ACR) traditional format criteria for Wegener’s granulomatosis (WG), the Sørensen criteria for WG and microscopic polyangiitis (MPA), and the Chapel Hill nomenclature for WG and MPA. Further, to develop and validate improved criteria for distinguishing WG from MPA by an artificial neural network (ANN) and by traditional approaches [classification tree (CT), logistic regression (LR)]. Methods All criteria were applied to 240 patients with WG and 78 patients with MPA recruited by a multicenter study. To generate new classification criteria (ANN, CT, LR), 23 clinical measurements were assessed. Validation was performed by applying the same approaches to an independent monocenter cohort of 46 patients with WG and 21 patients with MPA. Results A total of 70.8% of the patients with WG and 7.7% of the patients with MPA from the multi-center cohort fulfilled the ACR criteria for WG (accuracy 76.1%). The accuracy of the Chapel Hill criteria for WG and MPA was only 35.0% and 55.3% (Sørensen criteria: 67.2% and 92.4%). In contrast, the ANN and CT achieved an accuracy of 94.3%, based on 4 measurements (involvement of nose, sinus, ear, and pulmonary nodules), all associated with WG. LR led to an accuracy of 92.8%. Inclusion of antineutrophil cytoplasmic antibodies did not improve the allocation. Validation of methods resulted in accuracy of 91.0% (ANN and CT) and 88.1% (LR). Conclusion The ACR, Sørensen, and Chapel Hill criteria did not reliably separate WG from MPA. In contrast, an appropriately trained ANN and a CT differentiated between these disorders and performed better than LR.