Nomogram to Prognosticate Outcomes in Patients with Chronic Myeloid Leukemia At Any Time-Point During Tyrosine Kinase Inhibitor Therapy

Abstract Abstract 71 Background: The NCCN and the European LeukemiaNet guidelines for monitoring patients with chronic myeloid leukemia in chronic phase (CML-CP) provide recommendations for response assessment and treatment at 3, 6, 12, and 18 months based on evidence obtained in clinical trials. A clear limitation of such guidelines is their applicability at time-points different from those pre-specified. To overcome these limitations we have developed a novel statistical approach to CML prognostication. Method: In order to build our prognostic model, we used two cohorts of patients with CML-CP treated in the frontline DASISION phase III study (CA180-056) and the cohort of patients treated after imatinib failure in the dasatinib dose-optimization phase III study (CA180-034). Progression-free survival (PFS) was defined as any of the following: doubling of white cell count to >20×109/L in the absence of complete hematologic response (CHR); loss of CHR; increase in Ph+ BM metaphases to >35%; transformation to AP/BP; or death. A modified Cox proportional hazards model was used to build a prognostic nomogram. Results: A total of 1189 patients were used for this analysis: 519 from DASISION (259 dasatinib and 260 imatinib) and 670 from CA180-034. First, we devised a model to link a BCR-ABL1/ABL1 ratios (according to the International Standard) obtained at specific time points during the course of treatment with patientsO outcomes (PFS). For instance, at 18 months after front-line treatment, the future PFS probabilities are shown in Figure 1 A. At 6 months after second-line treatment, the future PFS probabilities are shown in Figure 1 B. Once the model was validated at specific time points, we next designed a nomogram to calculate patients’ outcomes at any time point during the course of therapy by plotting ‘master PFS curves' derived from the patient cohorts according to time. Figure 2 A&B give the 90% quantile of the remaining PFS for patients at any time after front-line and second-line treatment, respectively. These may be used a guideline for considering other treatment options when patients’ BCR-ABL1/ABL1 ratios exceed these values. Figure 2 shows that the remaining PFS times for either front- or second-line treated patients depend mostly on the current BCR-ABL/ABL ratio and less on the time at which the ratio is obtained, reflected by the fact that the curves showing future PFS probabilities are characterized by smooth slopes. Figure 2 A shows that 10% of front-line treated patients whose BCR-ABL1/ABL1 ratios are 50% or higher will have remaining PFS times of less than 12 months. If BCR-ABL1/ABL1 ratios are 75% or higher, then 10% of them will have remaining PFS times of less than 6 months. Similarly, Figure 2 B shows that for second-line treated patients whose BCR-ABL1/ABL1 ratios are 50% or higher, 10% of them will have remaining PFS time shorter than 6 months. Conclusion: We have designed a nomogram that predicts PFS for patients treated in the frontline and second line settings according to their BCR-ABL1/ABL1 ratios, independent from the time at which these ratios are obtained. A similar approach has been taken to predict failure-free and overall survival and will be presented at the meeting. This prognostic tool is readily available for clinical purposes and might greatly facilitate monitoring and prognostication in CML. Download : Download high-res image (21KB) Download : Download full-size image Download : Download high-res image (24KB) Download : Download full-size image Disclosures: No relevant conflicts of interest to declare.