Integration of Multiple Bioassays Using Machine Learning to Identify High-Risk CP-CML Patients Treated with Frontline Imatinib

Introduction. Imatinib has revolutionised the treatment of chronic phase-chronic myeloid leukemia (CP-CML), with up to 70% of patients (pts) achieving major molecular response (MMR, BCR-ABL1 < 0.1% IS). Achievement of MMR by 2 years (yrs) is associated with an excellent prospect of long term survival. Currently, three baseline prognostic scoring systems - the Sokal, Hasford (Euro) and EUTOS risk scores - have all been used to identify pts with a poor response and/or an adverse prognosis in CP-CML. Recently, the EUTOS long-term survival (ELTS) score is shown to have strong predictive power for overall survival in CML pts. We have previously reported bioassays that have significant value for predicting MMR. Combinations of these biomarkers, together with clinical risk score, may provide a better indicator of high risk pts at the time of diagnosis.