It is vital for physicians and persons with chronic myeloid leukemia (CML) to accurately predict the likelihood of achieving a major molecular response (MMR) and a deep molecular response (DMR; at least MR4) at the start of imatinib-therapy, which could help in decision making of treatment goals and strategies. To answer this question, we interrogated data from 1369 consecutive subjects with chronic phase CML receiving initial imatinib-therapy to identify predictive co-variates. Subjects were randomly-assigned to training (n = 913) and validation (n = 456) datasets. Male sex, higher WBC concentration, lower haemoglobin concentration, higher percentage blood blasts and larger spleen size were significantly-associated with lower cumulative incidences of MMR and MR4 in training dataset. Using Fine-Gray model, we developed the predictive scoring systems for MMR and MR4 which classified subjects into the low-, intermediate- and high-risk cohorts with significantly-different cumulative incidences of MMR and MR4 with good predictive discrimination and accuracy in training and validation cohorts with high area under the receiver-operator characteristic curve (AUROC) values. These data may help physicians decide appropriateness of initial imatinib therapy.
© 2022. The Author(s), under exclusive licence to Springer Nature Limited.