Model-based decision rules reduce the risk of molecular relapse after cessation of tyrosine kinase inhibitor therapy in chronic myeloid leukemia

• Published in: Blood Vol. 121; no. 2; pp. 378 - 384
• Main Authors: Horn, Matthias, Glauche, Ingmar, Müller, Martin C., Hehlmann, Rüdiger, Hochhaus, Andreas, Loeffler, Markus, Roeder, Ingo
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 10.01.2013
• Subjects: Antineoplastic Agents - administration & dosage; Benzamides; Fusion Proteins, bcr-abl - analysis; Fusion Proteins, bcr-abl - biosynthesis; Humans; Imatinib Mesylate; Leukemia, Myelogenous, Chronic, BCR-ABL Positive - drug therapy; Models, Theoretical; Neoplasm Recurrence, Local - prevention & control; Piperazines - administration & dosage; Polymerase Chain Reaction; Protein Kinase Inhibitors - administration & dosage; Pyrimidines - administration & dosage; Reverse Transcriptase Polymerase Chain Reaction; Risk Factors
• DOI: 10.1182/blood-2012-07-441956
• ISSN: 0006-4971; 1528-0020

Molecular response to imatinib (IM) in chronic myeloid leukemia (CML) is associated with a biphasic but heterogeneous decline of BCR-ABL transcript levels. We analyzed this interindividual heterogeneity and provide a predictive mathematical model to prognosticate the long-term response and the individual risk of molecular relapse on treatment cessation. The parameters of the model were determined using 7-year follow-up data from a randomized clinical trial and validated by an independent dataset. Our model predicts that a subset of patients (14%) achieve complete leukemia eradication within less than 15 years and could therefore benefit from discontinuation of treatment. Furthermore, the model prognosticates that 31% of the patients will remain in deep molecular remission (MR5.0) after treatment cessation after a fixed period of 2 years in MR5.0, whereas 69% are expected to relapse. As a major result, we propose a predictor that allows to assess the patient-specific risk of molecular relapse on treatment discontinuation and to identify patients for whom cessation of therapy would be an appropriate option. Application of the suggested rule for deciding about the time point of treatment cessation is predicted to result in a significant reduction in rate of molecular relapse. •BCR-ABL transcript dynamics in imatinib-treated chronic myeloid leukemia can consistently be described by a mathematical modeling approach.•Application of the model allows to predict the optimal time point for therapy stop as well as the risk of relapse in individual patients.