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  • 1
    In: Experimental Hematology, Elsevier BV, Vol. 41, No. 8 ( 2013-08), p. S46-
    Type of Medium: Online Resource
    ISSN: 0301-472X
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2013
    detail.hit.zdb_id: 2005403-8
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  • 2
    In: BMC Medical Informatics and Decision Making, Springer Science and Business Media LLC, Vol. 20, No. 1 ( 2020-12)
    Abstract: Individualization and patient-specific optimization of treatment is a major goal of modern health care. One way to achieve this goal is the application of high-resolution diagnostics together with the application of targeted therapies. However, the rising number of different treatment modalities also induces new challenges: Whereas randomized clinical trials focus on proving average treatment effects in specific groups of patients, direct conclusions at the individual patient level are problematic. Thus, the identification of the best patient-specific treatment options remains an open question. Systems medicine, specifically mechanistic mathematical models, can substantially support individual treatment optimization. In addition to providing a better general understanding of disease mechanisms and treatment effects, these models allow for an identification of patient-specific parameterizations and, therefore, provide individualized predictions for the effect of different treatment modalities. Results In the following we describe a software framework that facilitates the integration of mathematical models and computer simulations into routine clinical processes to support decision-making. This is achieved by combining standard data management and data exploration tools, with the generation and visualization of mathematical model predictions for treatment options at an individual patient level. Conclusions By integrating model results in an audit trail compatible manner into established clinical workflows, our framework has the potential to foster the use of systems-medical approaches in clinical practice. We illustrate the framework application by two use cases from the field of haematological oncology.
    Type of Medium: Online Resource
    ISSN: 1472-6947
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2046490-3
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  • 3
    In: Blood, American Society of Hematology, Vol. 121, No. 2 ( 2013-01-10), p. 378-384
    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 (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.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2013
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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  • 4
    Online Resource
    Online Resource
    American Society of Hematology ; 2006
    In:  Blood Vol. 108, No. 11 ( 2006-11-01), p. 2155-2155
    In: Blood, American Society of Hematology, Vol. 108, No. 11 ( 2006-11-01), p. 2155-2155
    Abstract: Treatment of chronic myeloid leukemia (CML) with the tyrosine kinase inhibitor imatinib represents a successful application of a molecularly targeted therapy. A rapid hematologic and cytogenetic response can be induced for the majority of patients even in advanced disease. However, the time course of disappearance of leukemia cells, characterized by the expression of the BCR-ABL fusion protein, varies between patients, and a complete eradication of the malignant cells is a rare event. The reasons for the heterogeneous response and the persistence of the malignant clone in many patients are currently not known. We propose a mathematical model which consistently explains short and long-term dynamics of BCR-ABL transcript levels in populations of CML patients under imatinib monotherapy. The model is based on the concept that normal and malignant cell clones compete for growth environments in which they behave slightly differently with regard to homing and cell cycle activation/deactivation. This concept has been successfully applied for understanding time-dependent chimerism in mice [Roeder et al.: Blood 105(2):609]. Applying the model to data sets from two independent cohorts of imatinib treated CML patients, we demonstrate the potential of our model to quantitatively describe the typical biphasic decline in BCR-ABL transcript levels during the first year of treatment. Besides the median transcript dynamics in the patient population the model is able to represent the heterogeneity in individual transcript time courses. Qualitative differences in the imatinib response are explained by small quantitative differences in the drug effects regarding proliferation inhibition and/or induction of apoptosis for BCR-ABL positive cells. As demonstrated by comparison with five years follow-up data of 69 unselected newly diagnosed CML patients recruited into the IRIS trial in Germany [Mueller et al.: Leukemia 17(12):2392] the model also correctly describes long-term BCR-ABL dynamics. The observed median BCR-ABL transcript levels, including the vanishing decline after year four of treatment, can quantitatively be explained by a decreasing treatment efficiency in a subset of patients, potentially caused by imatinib-resistant clones. Sensitivity analyses show that moderate functional differences of the resistance mutations can lead to remarkable differences in long-term treatment efficiency. On the other hand, in patients not developing resistance mutations our model predicts the general chance of an eradication of the malignant clone in the long run. This is supported by data in a patient subgroup showing a continued decline of BCR-ABL transcript levels over five years of treatment. Beyond the consistent description of the clinically observed BCR-ABL dynamics we provide testable predictions for effects of different combination treatments. Based on the explanation of CML as a clonal competition of malignant and normal hematopoietic stem cells, our model particularly predicts that the therapeutic benefit of imatinib can be augmented by a combination with proliferation stimulating treatment strategies. In addition the model permits to describe the heterogeneity of the effect of resistance mutations with respect to specific treatment strategies. In summary, our model describes CML dynamics under imatinib therapy with potential implications for the design of future treatment strategies.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
    RVK:
    RVK:
    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2006
    detail.hit.zdb_id: 1468538-3
    detail.hit.zdb_id: 80069-7
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  • 5
    Online Resource
    Online Resource
    S. Karger AG ; 2008
    In:  Cells Tissues Organs Vol. 188, No. 1-2 ( 2008), p. 236-247
    In: Cells Tissues Organs, S. Karger AG, Vol. 188, No. 1-2 ( 2008), p. 236-247
    Abstract: Chronic myeloid leukemia (CML) is a clonal hematopoietic disorder induced by translocation of chromosomes 9 and 22, resulting in an overproduction of myeloid blood cells. CML-specific characteristics include a latency time of several years, a period of coexistence of malignant and normal cells and an eventual dominance of the malignant clone. Different drug therapies are available, most notably imatinib, which inhibits the oncogenic 〈 i 〉 BCR-ABL1 〈 /i 〉 tyrosine kinase. Although the chromosomal aberration causing CML is well known, the resulting dynamic effects on the system behavior are not sufficiently understood yet. Here, we apply an already established mathematical model of hematopoietic stem cell organization. Based on parameter estimates for normal hematopoiesis, we systematically explore the changes in these parameters necessary to reproduce CML-specific characteristics regarding emergence and course of disease as well as a variety of qualitative and quantitative clinical data on CML treatment. Our results indicate that 1 or more of the following mechanisms are compatible with the induction of a dominant clone in the proposed model: a retarded differentiation process, a reduced turnover time or a defective cell-microenvironment interaction of the neoplastic cells. However, in order to explain the massive overproduction of malignant cells, an unregulated and abnormal activation of leukemia stem cells into cycle has to be assumed additionally. Based on our simulation results we conclude that CML dynamics can most appropriately be explained by a modulation of the cell-microenvironment interactions of leukemia stem cells, including both the process of stem cell silencing and activation into cycle.
    Type of Medium: Online Resource
    ISSN: 1422-6405 , 1422-6421
    Language: English
    Publisher: S. Karger AG
    Publication Date: 2008
    detail.hit.zdb_id: 1481840-1
    SSG: 12
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  • 6
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2009
    In:  Bulletin of Mathematical Biology Vol. 71, No. 3 ( 2009-4), p. 602-626
    In: Bulletin of Mathematical Biology, Springer Science and Business Media LLC, Vol. 71, No. 3 ( 2009-4), p. 602-626
    Type of Medium: Online Resource
    ISSN: 0092-8240 , 1522-9602
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2009
    detail.hit.zdb_id: 1462512-X
    SSG: 12
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  • 7
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2006
    In:  Nature Medicine Vol. 12, No. 10 ( 2006-10), p. 1181-1184
    In: Nature Medicine, Springer Science and Business Media LLC, Vol. 12, No. 10 ( 2006-10), p. 1181-1184
    Type of Medium: Online Resource
    ISSN: 1078-8956 , 1546-170X
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2006
    detail.hit.zdb_id: 1484517-9
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