Risk Score at Diagnosis and the Dynamics of Response to TKI Therapy In Chronic Myeloid Leukemia.

Abstract 1236 Background: Although most patients with early chronic phase CML (ECP-CML) respond to TKI therapy, the depth and speed of response can be different. While it is known that both the Sokal and Hasford scores have an impact on the speed and depth of response, no mechanisms explaining these differences have been identified. Objective: To provide explanations for any potential differences in CML response as a function of the Sokal and Hasford score using a computational model. Methods: We utilize a computational model of hematopoiesis and CML, together with serial quantitative data of disease burden under nilotinib therapy to determine the fraction of CML cells responding to therapy (z) and the impact of TKI on the self-renewal probability of CML cells (e) under therapy. Patients were stratified at diagnosis on both the Sokal and Hasford scoring system. A non-linear least squares method was used to separately fit the model to serial Q-RT-PCR data for BCR-ABL in response to therapy in each cohort. Results: A total of 73 patients were studied. The number of patients with low, intermediate and high risk disease based on the Sokal score was 34, 29 and 10 respectively while the respective distribution of patients on the Hasford score was 29, 43 and 1. Although the impact of nilotinib on the self-renewal probability of CML progenitor cells was similar across all risk groups (there were substantial differences in the fraction of cells responding to therapy: For the Sokal groups, the fraction of cells (z) responding to therapy decreased from 0.09 to 0.086 and 0.069 respectively for low, intermediate and high risk disease. In the case of the Hasford score, the difference in z between low and intermediate categories becomes more pronounced, i.e. z is 0.093 for low and 0.08 for intermediate risk disease. Conclusions: The risk score at diagnosis of CML has a direct impact on the dynamics of response to TKI therapy. Patients with a lower risk score respond faster to the same therapy when compared to high risk patients. The impact of TKI on the self renewal of CML cells appears to be the same regardless of the risk score but the fraction of cells responding decreases as the risk score increases. This suggests that subclones that may be less sensitive to TKI therapy may be emerging. Strategies that increase the fraction of cells responding to therapy in patients with higher risk disease may be indicated. Disclosures: Rosti: Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bristol Myers Squibb: Honoraria, Speakers Bureau; Roche: Speakers Bureau.