Enrica Antonia Martino, Santino Caserta, Ernesto Vigna, Antonella Bruzzese, Maria Eugenia Alvaro, Nicola Amodio, Eugenio Lucia, Virginia Olivito, Caterina Labanca, Francesco Mendicino, Mamdouh Skafi, Valter Gattei, Fortunato Morabito, Massimo Gentile
The integration of measurable residual disease (MRD) into the management of chronic lymphocytic leukemia (CLL) has emerged as a major advance in risk stratification and trial design, particularly in the context of time-limited, targeted regimens. High-sensitivity MRD assessment, enabled by multicolor flow cytometry, allele-specific oligonucleotide PCR, and next-generation sequencing (NGS), provides a robust, quantifiable measure for depth of remission and long-term outcomes. Landmark trials-including CLL14, MURANO, CAPTIVATE, and GLOW-have consistently demonstrated that achieving undetectable MRD (uMRD) strongly predicts prolonged progression-free survival (PFS) and overall survival (OS), within a range of chemoimmunotherapy and venetoclax-based time-limited regimens. In selected clinical trials, MRD assessment has been prospectively incorporated into strategies exploring time-limited therapy and MRD-adapted discontinuation, although routine MRD-guided decision-making in clinical practice remains investigational. CLL research is increasingly focused on treatment-free observation in select patients achieving deep and sustained remissions, with MRD playing a central prognostic role. Emerging technologies, including circulating tumor DNA (ctDNA) monitoring and artificial intelligence (AI)-driven predictive modeling, promise to further refine risk stratification and personalize therapy. This review summarizes the current evidence supporting MRD as a prognostic biomarker and clinical trial endpoint, discusses investigational MRD-adapted strategies, and outlines future directions-including ctDNA and AI-based tools-that may ultimately support more individualized treatment duration and treatment-free observation in CLL.