Leukemia: Reduction Ratio and Halving Time of BCR: : ABL1 IS Transcript Levels

Abstract

Objective: Achieving an early molecular response (EMR) is crucial for improving the prognosis of patients with chronic myeloid leukemia (CML). The halving time (HT) and reduction ratio (RR) of BCR::ABL1 transcript levels have recently emerged as additional prognostic indexes besides the BCR::ABL1 International Scale (IS). We aimed to investigate the prognostic role of BCR::ABL1 transcript levels, HT, and RR on molecular response kinetics at 3 months in patients with newly diagnosed chronic-phase (CP)-CML. Materials and Methods: Forty patients with CP-CML who received first-line imatinib treatment were included in this study. BCR::ABL1 transcript levels and molecular responses at baseline and at 3, 6, 12, and 24 months of treatment were evaluated retrospectively. Major molecular response (MMR) at 12 months and event-free survival (EFS) were determined as primary endpoints and the effects of treatment kinetics on these parameters were examined. Results: Of the 40 patients, BCR::ABL1 IS was ≤10% at 3 months in 72.5%, representing EMR. The rate of event occurrence was 45.5% in patients with BCR::ABL1 IS of >10%, whereas it was 6.9% in those with BCR::ABL1 IS of ≤10% (p=0.004). MMR was detected in 62.1% of the patients with EMR and in 9.1% of those without EMR (p=0.003). The cut-off value for achieving MMR was 24 days for HT and 0.04 for RR. Deep molecular response (DMR) at 24 months was associated with HT of ≤24 days and RR of ≤0.04. EFS was found to be significantly better in the group with BCR::ABL1 IS of ≤10% and HT of ≤24 days (p=0.001) and in the group with BCR::ABL1 IS of ≤10% and RR of ≤0.04 (p=0.007) compared to others. Conclusion: Our findings revealed that MMR could be predicted via EMR as well as by HT and RR. Additionally, HT of ≤24 days and RR of ≤0.04 were more important than BCR::ABL1 IS of ≤10% in achieving DMR at 24 months, and the combination of BCR::ABL1 IS of ≤10% with both HT of ≤24 days and RR of ≤0.04 has the best predictive value for EFS.