The Predictive Role of Symptoms/signs on ACR20 Responses in Rheumatoid Arthritis Analyzed with Data Mining Approaches

Objective: The role of symptoms/signs for American College of Rheumatology 20% response (ACR20) prediction in rheumatoid arthritis (RA) analyzed with decision tree and neuron network was explored. Methods: 489 patients were randomly divided to receive Western medicine (WM) therapy, 247 cases; and traditional Chinese medicine (CM) therapy (TCM), 242 cases. ACR20 response was employed as effectiveness evaluation point. The symptoms/signs at baseline were collected and analyzed for ACR20 response prediction with decision tree and neural network methods, and 75% data were for training and 25% data for verification set. Results: 19 symptoms/signs in CM treated patients and 26 in WM treated patients were obtained from MANTELHAENSZEL test or Fisher's exact test (p