Gene expression classifier for prediction of end-induction (day 29) flow MRD in pretreatment samples combined with the gene expression classifier for RFS. (A) A ROC shows the high accuracy of the 23-probe-set MRD classifier (LOOCV error rate of 24.61%; sensitivity 71.64%, specificity 77.42%) in predicting MRD. The area under the ROC curve (0.80) is significantly greater than an uninformative ROC curve (0.5; P < .001). (B) Heatmap of 23-probe-set predictor of MRD presented in rows (false discovery rate < .001%, SAM). The columns represent patient samples with positive or negative end-induction flow MRD, whereas the rows are the specific predictor genes. Red: high expression relative to the mean; green: low expression relative to the mean. (C) Kaplan-Meier estimates of RFS for the risk groups determined by combining the gene expression classifiers for RFS and MRD, analogous to Figure 2E, with the gene expression predictor for MRD replacing day 29 flow MRD. The 3 risk groups have significantly different RFS (log rank test, P < .001).