Cases identified for further imaging were assessed by four binary measures: sensitivity = number of TP/number of cancer cases; specificity = number of TN/number of non-cancer cases; positive predictive value (PPV) = number of cancer cases/(number of TP + FP cases); and negative predictive value (NPV) = number of non-cancer cases/(number of FN + TN). Random-effect logistic regression models were used to test whether each binary measure differed significantly between mammography plus AWBU versus mammography alone. To account for the MRMC framework, we included random effects for readers and cases similar to the DBM model [15].