Literature DB >> 23175686

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

Matthias Horn1, Ingmar Glauche, Martin C Müller, Rüdiger Hehlmann, Andreas Hochhaus, Markus Loeffler, Ingo Roeder.   

Abstract

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 (MR(5.0)) after treatment cessation after a fixed period of 2 years in MR(5.0), 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.

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Year:  2012        PMID: 23175686     DOI: 10.1182/blood-2012-07-441956

Source DB:  PubMed          Journal:  Blood        ISSN: 0006-4971            Impact factor:   22.113


  25 in total

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2.  The role of Fas-associated phosphatase 1 in leukemia stem cell persistence during tyrosine kinase inhibitor treatment of chronic myeloid leukemia.

Authors:  W Huang; C-H Luan; E E Hjort; L Bei; R Mishra; K M Sakamoto; L C Platanias; E A Eklund
Journal:  Leukemia       Date:  2016-03-17       Impact factor: 11.528

Review 3.  Modeling head and neck cancer stem cell-mediated tumorigenesis.

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4.  Differential response to cytotoxic therapy explains treatment dynamics of acute myeloid leukaemia patients: insights from a mathematical modelling approach.

Authors:  H Hoffmann; C Thiede; I Glauche; M Bornhaeuser; I Roeder
Journal:  J R Soc Interface       Date:  2020-09-09       Impact factor: 4.118

5.  An integrated computational model of the bone microenvironment in bone-metastatic prostate cancer.

Authors:  Arturo Araujo; Leah M Cook; Conor C Lynch; David Basanta
Journal:  Cancer Res       Date:  2014-05-01       Impact factor: 12.701

6.  Predicting Time to Relapse in Acute Myeloid Leukemia through Stochastic Modeling of Minimal Residual Disease Based on Clonality Data.

Authors:  Khanh N Dinh; Roman Jaksik; Seth J Corey; Marek Kimmel
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7.  A Review of Mathematical Models for Leukemia and Lymphoma.

Authors:  Geoffrey Clapp; Doron Levy
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8.  Imatinib withdrawal syndrome and longer duration of imatinib have a close association with a lower molecular relapse after treatment discontinuation: the KID study.

Authors:  Sung-Eun Lee; Soo Young Choi; Hye-Young Song; Soo-Hyun Kim; Mi-Yeon Choi; Joon Seong Park; Hyeoung-Joon Kim; Sung-Hyun Kim; Dae Young Zang; Sukjoong Oh; Hawk Kim; Young Rok Do; Jae-Yong Kwak; Jeong-A Kim; Dae-Young Kim; Yeung-Chul Mun; Won Sik Lee; Myung Hee Chang; Jinny Park; Ji Hyun Kwon; Dong-Wook Kim
Journal:  Haematologica       Date:  2016-02-17       Impact factor: 9.941

9.  Computational modeling reveals a key role for polarized myeloid cells in controlling osteoclast activity during bone injury repair.

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10.  Significance of deeper molecular responses in patients with chronic myeloid leukemia in early chronic phase treated with tyrosine kinase inhibitors.

Authors:  Lorenzo Falchi; Hagop M Kantarjian; Xuemei Wang; Dushyant Verma; Alfonso Quintás-Cardama; Susan O'Brien; Elias J Jabbour; Farhad Ravandi-Kashani; Gautam Borthakur; Guillermo Garcia-Manero; Srdan Verstovsek; Jan A Burger; Raja Luthra; Jorge E Cortes
Journal:  Am J Hematol       Date:  2013-09-12       Impact factor: 10.047

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