Evaluation of the relationship between tyrosine kinase inhibitor treatment responses and complete blood count parameters in patients with chronic myeloid leukemia

Chronic Myeloid Leukemia (CML) is a hematologic malignancy that can be effectively treated with tyrosine kinase inhibitors (TKIs); however, early identification of patients who may have suboptimal responses to treatment remains a significant clinical challenge. In this context, this study aimed to evaluate the discriminative power of complete blood count (CBC)-derived inflammatory markers—namely, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic inflammation index (SII), and systemic inflammation response index (SIRI)—in predicting early and long-term molecular responses to TKI therapy in CML patients. A retrospective analysis was conducted on 43 patients diagnosed with chronic-phase CML who were treated with either first- or second-generation TKIs. Inflammatory parameters derived from CBC at diagnosis were analyzed, and treatment responses were assessed at the 3rd, 6th, and 12th months, as well as during follow- up (final measurement during follow-up) after the 12th month. ROC analysis was used to evaluate the discriminative performance of the parameters. According to the results, NLR (p= 0.0112) and SIRI (p= 0.0066) were found to be significant discriminators of treatment response at the 3rd month (AUC= 0.725 and 0.743, respectively), and SIRI (p= 0.0332) maintained its discriminative ability at the 6th month. None of the parameters demonstrated significance at the 12th month. However, PLR (p= 0.0013) and SIRI (p= 0.0066) were significant in distinguishing final treatment response (AUC= 0.756 and 0.731, respectively). Elevated baseline CBC-derived markers were significantly associated with suboptimal early treatment response (p<0.05), and the multivariate analysis confirmed their role as independent discriminators. These findings suggest that CBC-based inflammatory markers may serve as accessible, low-cost, and practical tools to aid clinical decision-making by predicting poor response risk in patients undergoing TKI therapy for CML.