Table 4.

ALL subgroup prediction accuracies using top 50 chi-square selected genes from U133A and B and artificial neural network (ANN) in decision tree format



Training set, %*


Test set, %

Subgroup
Apparent accuracy
True accuracy§
Sensitivity
Specificity
T-ALL  100   100   100   100  
E2A-PBX1  100   100   100   100  
TEL-AML1  98   100   100   100  
BCR-ABL  100   95   75   100  
MLL rearrangement   100   100   100   100  
Hyperdiploid with more than 50 chromosomes
 
100
 
100
 
100
 
100
 


Training set, %*


Test set, %

Subgroup
Apparent accuracy
True accuracy§
Sensitivity
Specificity
T-ALL  100   100   100   100  
E2A-PBX1  100   100   100   100  
TEL-AML1  98   100   100   100  
BCR-ABL  100   95   75   100  
MLL rearrangement   100   100   100   100  
Hyperdiploid with more than 50 chromosomes
 
100
 
100
 
100
 
100
 
*

Training set consisted of 100 cases with distribution: 12 T-ALL, 13 E2A-PBX1, 15 TEL-AML1, 11 BCR-ABL, 15 MLL, 13 hyperdiploid with more than 50 chromosomes, and 21 other.

Blinded test set consisted of 32 cases (2 T-ALL, 5 E2A-PBX1, 5 TEL-AML1, 4 BCR-ABL, 5 MLL, 4 hyperdiploid more than 50, and 7 other).

Apparent accuracy determined by 3-fold cross-validation.

§

True accuracy determined by class prediction on the blinded test set.

Sensitivity indicates (the number of positive cases predicted)/(the number of true positives).

Specificity indicates (the number of negative cases predicted)/(the number of true negatives).

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