Objective helene.hoffmann@tu-dresden.de http://tu-dresden.de/med/imb Contact Helene Hoffmann Institute for Medical Informatics and Biometry Medizinische Fakultät Carl Gustav Carus Technische Universität Dresden HaematoOPT is funded via the BMBF 0 500 1000 1500 2000 time [days] 10-2 100 102 NPM1/Abl [%] 0 500 1000 time [days] 10-2 100 102 NPM1/Abl [%] Correlation of relapse time and parameters Measurement error and time Relapse prediction A Ω LA HA LO HO KA KO ↯ X ⟳ph ↯ X ⟳pl tlo therapy action - leukemic - healthy tla tho tha dl dh cl ch quiescent stem cells cycling stem cells A Mathematical Model for Relapse Prediction in AML Patients Based on Continuing NPM1 Measurements H. Hoffmann1, I. Glauche1, C. Thiede2, M. Bornhäuser2, M. Kramer2, C. Röllig2, I. Roeder1,3 1Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, TU Dresden, Germany 2Medizinische Klinik und Poliklinik I, Faculty of Medicine Carl Gustav Carus, TU Dresden, Germany 3National Center for Tumor Diseases (NCT), Partner Site Dresden, Dresden, Germany In order to detect minimal residual disease (MRD) with high sensitivity in AML patients it is necessary to monitor molecular leukemia markers, such as mutations in the NPM1 gene (Shayegi 2013, Blood), which occur in about one third of AML patients (Falini 2005, N Engl J Med). Today the relative NPM1 abundance in the bone marrow is routinely used for relapse detection (Gorello 2006, Leukemia; Papadaki 2009, Br J Haematol.). For more precise relapse time predictions to improve individual treatment strategies and final outcome we developed a mathematical model describing the effected stem cell compartment in the bone marrow and used the NPM1 measurement data for individual relapse predictions. Furthermore, we analysed the impact of measurement error and time point of measurements on the prediction accuracy. Clinical data Example fits Available data set for our study: Number of patients 271 Number of relapsed patients 74 Median Age 53 (20-79) Median number of measurements 5 (3-21) Median number of therapy cycles 4 (1-10) - AML2003 (NCT00180102) - AML60+ (NCT00180167) Clinical trials: Bone marrow NPM1 time courses of AML patients: of the Study Alliance Leukemia Conclusions The developed mathematical model is able to reproduce the decline of leukemic burden, remission and molecular relapse of AML patients. The individual patients' model parameters are strongly connected with their time of relapse and they can be used for estimating relapse probabilities. Theoretical analyses showed that individual relapse time prediction can be strongly improved by reducing the measurement error and by increasing the measurement frequency. to - activation rate ta - inactivation rate p - proliferation rate c - therapeutic kill rate d - differentiation rate K - capacity Mathematical model ˙XA = Inactivation −Activation ˙XO = Activation−Inactivation+Proliferation−Differentiation−TherapyKill • two bone marrow compartments: one with quiescent (A) and one with cycling cells (Ω) • cells switch between compartments • therapy kill acts only on cells in Ω • leukemic and healthy cells compete for bone marrow space • leukemic cells proliferate faster, are faster activated and slower inactivated Model assumptions: - AMLRegistry High vs. low parameters: 0 5 10 15 20 25 tl o/pl 0 0.2 0.4 0.6 0.8 1 one-year relapse probability no relapse relapse Probability of relapsing within the first year using relapse information from data: Low activation and high proliferation of leukemic cells is connected to earlier relapse. Using the leukemic activation to proliferation ratio a probability of relapsing within one year can be estimated. Low pl High pl 0 500 1000 1500 2000 relapse time [days] Low tl o High tl o 0 500 1000 1500 2000 relapse time [days] p-value < 0.001 p-value < 0.001 U-test Fitting leukemic activation (tlo) and proliferation (pl) to the data: best fit to complete data best fit to first 9 months corresp. 95% confidence