Application of an artificial neural network in the prognosis of chronic myeloid leukemia.

OBJECTIVE

To use a commercially available artificial neural network (ANN) software program to distinguish prognostically good and bad cases of chronic myeloid leukemia (CML).

STUDY

DESIGN

A total of 40 patients with CML who developed blast crisis or proceeded in the accelerated phase were selected. They formed two groups, group 1 and group 2, of 20 patients each, who developed accelerated phase or blast crisis within 18 months or 30 months, respectively, after the initial diagnosis of the chronic phase of CML. The detailed clinical, hematologic, and morphometric data were collected in all these cases. A suitable ANN software program was used to analyze these data.

RESULTS

All cases were randomly distributed automatically by the program into three groups: training set (28), validation set (4), and test set (8). In the test set, the ANN program successfully classified all group I and group II patients.

CONCLUSION

We successfully used a commercially available ANN software program to develop a model able to classify prognostically good and bad cases of CML.