ELN milestone-driven TKI switching improves deep molecular response rates in chronic myeloid leukemia
Abstract
Abstract Background: Deep molecular response (DMR) is a prerequisite for successful treatment-free remission (TFR) in patients with chronic myeloid leukemia in chronic phase (CML-CP) on tyrosine kinase inhibitor (TKI) therapy. Achievement of an optimal molecular response at the 3-, 6-, and 12-month European LeukemiaNet (ELN) milestones is an independent predictor of deep molecular response (DMR). This study evaluated whether a prospective, milestone-driven strategy of switching TKIs for suboptimal responders improves deep molecular response (DMR) rates compared to those of a historical cohort. Methods: This single-center study compared a prospectively managed cohort (n=36, diagnosed 2021–2023) with a historical control cohort (n=436, diagnosed before 2020). In the prospective cohort, patients failing to achieve ELN optimal milestones (e.g., BCR-ABL1>10% at M3, BCR-ABL1 >1% at M6, or BCR-ABL1 > 0.1% at M12) were promptly switched to an alternative TKI. The historical cohort received standard of care without this structured intervention protocol. The primary endpoint was the DMR (BCR-ABL1 ≤0.0032%) rate at 12 months (M12). Secondary endpoints included rates of TFR in patients who achieved ELN milestone responses before TKI discontinuation Results: Despite the prospective cohort being significantly older (median age 46.5 vs. 37 years, p=0.002) and having a higher proportion of high Sokal risk patients (19.4% vs. 5.5%, p=0.016), it demonstrated superior outcomes. The proactive strategy led to a significantly shorter median time to TKI switch for non-responders (4 vs. 21 months, p=0.003) and a faster time to achieve MMR (6 vs. 14 months, p<0.001). Consequently, the 12-month MMR and DMR rate was more than threefold higher in the prospective cohort than in the historical cohort (75% vs. 43.7%, p<0.001 and 42.5% vs. 13.8%, p<0.001), respectively. Achievement rates for ELN milestones were similar trend at M3 (61.1% vs. 45.4%, p=0.07), but consistently higher in the prospective group at M6 (66.7% vs. 43.6%, p=0.007) and M12 (75.0% vs. 49.7%, p=0.004) after early switch TKI strategy. Across both cohorts, achieving M3 and M6 milestones was strongly associated with higher rates of subsequent DMR and TFR eligibility. We further analyze TFR outcomes in 34 patients who achieved European LeukemiaNet (ELN) milestone responses at 3, 6 and 12 months of TKI therapy. Before discontinuation, the median duration of sustained DMR was 57 months (range 24–140), and the median total TKI exposure was 84 months (range 44–172). After stopping TKI, the median TFR duration was 26 months (range 2–115), and the projected 1-year TFR rate reached 64.7%. These findings indicate that ELN milestone-guided management not only increases the probability of achieving DMR but also translates into improved TFR success. Conclusions: A prospective, milestone-driven management strategy, including prompt TKI switching for suboptimal responders, significantly accelerates response and increases the rate of DMR in CML-CP patients. This real-world evidence underscores the prognostic value of early ELN milestones and supports their use as actionable triggers for treatment optimization to improve long-term outcomes, including TFR potential. Keywords: chronic myeloid leukemia, ELN milestones, deep molecular response, TKI switching
Article Details
Authors (13)
Lisi Huang
1Department of Hematology, Guangdong Provincial People′s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, guangzhou, China
Chengxin Deng
Key Laboratory of Artificial Microstructures in Yunnan Higher Education Institutions, School of Physics Science and Technology, Kunming University 1 , 650214 Kunming,
Zesheng Lu
Minming Li
1Department of Hematology, Guangdong Provincial People′s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, guangzhou, China
Ping Wu
Department of Neurobiology, University of Texas Medical Branch
Suxia Geng
1Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Department of Hematology, Guangzhou, China
Yulian Wang
Lingji Zeng
1Department of Hematology, Guangdong Provincial People′s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, guangzhou, China
Qiong Luo
Center for Computational Quantum Chemistry, School of Chemistry, South China Normal University
Xin Huang
Peilong Lai
Xin Du
State Key Laboratory of Immune Response and Immunotherapy, Department of Rheumatology and Immunology, The First Affiliated Hospital of University of Science and Technology of China, Center for Advanced Interdisciplinary Science and Biomedicine of IHM, Division of Life Sciences and Medicine, University of Science and Technology of China
Jianyu Weng
5Department of Hematology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China