Evolving Therapeutic Algorithms in Chronic Myeloid Leukemia: Integrating Efficacy, Safety, and Survivorship.

Chronic myeloid leukemia (CML) has undergone a significant shift over the past two decades, transitioning from a fatal malignancy to a chronic, highly manageable disease with near-normal life expectancy for most patients. This transformation has been driven by the development of BCR-ABL1-targeted tyrosine kinase inhibitors (TKIs), which have enabled durable disease control and deep molecular responses (DMRs) in the majority of patients with chronic-phase CML. As long-term survival outcomes have plateaued across available agents, contemporary management has shifted beyond disease suppression toward optimizing long-term safety, quality of life, and the achievement of treatment-free remission (TFR). This review summarizes current evidence on molecular monitoring strategies, the comparative efficacy and toxicity profiles of first-, second-, and third-generation TKIs, and emerging advances in response assessment. Patient-centered TKI selection is discussed in the context of cardiovascular risk, comorbidities, treatment tolerability, and survivorship goals, reflecting the growing emphasis on individualized therapy in chronic-phase CML. Molecular monitoring strategies are examined in parallel, highlighting the clinical importance of early and sustained DMRs in guiding therapeutic decisions and TFR eligibility. Although RT-qPCR remains the standard for molecular monitoring, emerging high-sensitivity techniques such as digital droplet PCR and next-generation sequencing provide complementary value by improving the detection of low-level residual disease, refining risk stratification, and enabling earlier identification of resistance. Emerging therapeutic strategies and advances in response assessment further highlight ongoing efforts to enhance the depth and durability of remission while minimizing long-term toxicity. These developments support a more precise, individualized, and outcome-driven approach to modern CML management.