Background: Outcomes in chronic myeloid leukemia (CML) remain heterogeneous despite effective BCR::ABL1 tyrosine kinase inhibitors (TKIs). Somatic mutations in epigenetic regulators, particularly additional sex combs-like 1 (ASXL1), have been implicated in adverse prognosis, but their clinical impact in CML has not been systematically defined. Methods: A systematic review was conducted using CINAHL, EMBASE, MEDLINE Ultimate, and PubMed from inception through August 2025. A total of 1339 records were identified; the eligible studies included adult and pediatric patients with chronic and advanced-phase (accelerated or blast) CML. After duplicate removal and screening, 11 studies met the inclusion criteria; these included adult patients only and were included in a qualitative synthesis and meta-analysis. ASXL1 mutation status was assessed using validated molecular methods. The outcomes included the molecular response, cytogenetic response, survival, and treatment resistance. Random-effects models were used to calculate the pooled odds ratios (ORs) with 95% confidence intervals (CIs). Statistical heterogeneity was assessed using the I2 statistic. Results: Across the included studies, ASXL1 mutations were detected in approximately 15% of patients. At 12 months, patients with ASXL1 mutations had significantly lower odds of achieving a major molecular response (MMR) compared with ASXL1-wildtype patients (OR 0.29; 95% CI 0.16–0.51; p < 0.0001; I2 = 30%). No statistically significant difference was observed in the complete cytogenetic response (CCyR) (OR 0.30; 95% CI 0.02–5.31; p = 0.41; I2 = 68%). Compared with patients harboring other non-ASXL1 somatic mutations, an ASXL1 mutation was not associated with a significant difference in MMR (OR 0.49; 95% CI 0.23–1.05; p = 0.067; I2 = 0%). Conclusions: ASXL1 mutations may be associated with an inferior molecular response to TKI therapy in CML, supporting their role as an adverse prognostic biomarker. These findings highlight the potential value of incorporating myeloid mutation profiling into future CML risk-stratification strategies.
Ahmad et al. (Wed,) studied this question.