Figure 3

Comparisons of the specificity and sensitivity of logistic regression models. Data from quantitative ELISAs for three antibodies were evaluated for ability to predict disease. Lower curve: predictive accuracy using the logistic regression model with RELT data alone from 87 patients and from 87 normal persons as the explanatory variable. The area under the curve is 0.727 and the model is significant (P = 0.0001). Upper curve: predictive accuracy with the combination of ASB-9, SERAC1, and RELT as explanatory variables, where P = 0.0001 and the area under the curve is 0.861.