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      Optimized and Personalized Phlebotomy Schedules for Patients Suffering From Polycythemia Vera

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          Abstract

          Polycythemia vera (PV) is a slow-growing type of blood cancer, where the production of red blood cells (RBCs) increase considerably. The principal treatment for targeting the symptoms of PV is bloodletting (phlebotomy) at regular intervals based on data derived from blood counts and physician assessments based on experience. Model-based decision support can help to identify optimal and individualized phlebotomy schedules to improve the treatment success and reduce the number of phlebotomies and thus negative side effects of the therapy. We present an extension of a simple compartment model of the production of RBCs in adults to capture patients suffering from PV. We analyze the model's properties to show the plausibility of its assumptions. We complement this with numerical results using exemplary PV patient data. The model is then used to simulate the dynamics of the disease and to compute optimal treatment plans. We discuss heuristics and solution approaches for different settings, which include constraints arising in real-world applications, where the scheduling of phlebotomies depends on appointments between patients and treating physicians. We expect that this research can support personalized clinical decisions in cases of PV.

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          Most cited references29

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          On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming

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            Prediction of blood volume in normal human adults.

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              Philadelphia-negative classical myeloproliferative neoplasms: critical concepts and management recommendations from European LeukemiaNet.

              We present a review of critical concepts and produce recommendations on the management of Philadelphia-negative classical myeloproliferative neoplasms, including monitoring, response definition, first- and second-line therapy, and therapy for special issues. Key questions were selected according the criterion of clinical relevance. Statements were produced using a Delphi process, and two consensus conferences involving a panel of 21 experts appointed by the European LeukemiaNet (ELN) were convened. Patients with polycythemia vera (PV) and essential thrombocythemia (ET) should be defined as high risk if age is greater than 60 years or there is a history of previous thrombosis. Risk stratification in primary myelofibrosis (PMF) should start with the International Prognostic Scoring System (IPSS) for newly diagnosed patients and dynamic IPSS for patients being seen during their disease course, with the addition of cytogenetics evaluation and transfusion status. High-risk patients with PV should be managed with phlebotomy, low-dose aspirin, and cytoreduction, with either hydroxyurea or interferon at any age. High-risk patients with ET should be managed with cytoreduction, using hydroxyurea at any age. Monitoring response in PV and ET should use the ELN clinicohematologic criteria. Corticosteroids, androgens, erythropoiesis-stimulating agents, and immunomodulators are recommended to treat anemia of PMF, whereas hydroxyurea is the first-line treatment of PMF-associated splenomegaly. Indications for splenectomy include symptomatic portal hypertension, drug-refractory painful splenomegaly, and frequent RBC transfusions. The risk of allogeneic stem-cell transplantation-related complications is justified in transplantation-eligible patients whose median survival time is expected to be less than 5 years.
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                Author and article information

                Contributors
                Journal
                Front Physiol
                Front Physiol
                Front. Physiol.
                Frontiers in Physiology
                Frontiers Media S.A.
                1664-042X
                17 April 2020
                2020
                : 11
                : 328
                Affiliations
                [1] 1Institute for Mathematical Optimization, Otto-von-Guericke-University Magdeburg , Magdeburg, Germany
                [2] 2Department of Hematology and Oncology, Medical Center, Otto-von-Guericke-University Magdeburg , Magdeburg, Germany
                Author notes

                Edited by: Julio R. Banga, Spanish National Research Council, Spain

                Reviewed by: Alexey Goltsov, Abertay University, United Kingdom; Francesco Passamonti, University of Insubria, Italy; Matthew Joseph Simpson, Queensland University of Technology, Australia

                *Correspondence: Patrick Lilienthal patrick-marcel.lilienthal@ 123456ovgu.de

                This article was submitted to Systems Biology, a section of the journal Frontiers in Physiology

                †These authors have contributed equally to this work

                Article
                10.3389/fphys.2020.00328
                7180210
                32362837
                cc6db5cd-6dbb-41d6-a388-661bab822f91
                Copyright © 2020 Lilienthal, Tetschke, Schalk, Fischer and Sager.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 21 December 2019
                : 20 March 2020
                Page count
                Figures: 7, Tables: 6, Equations: 17, References: 42, Pages: 19, Words: 13178
                Funding
                Funded by: European Research Council 10.13039/501100000781
                Award ID: 647573
                Funded by: European Regional Development Fund 10.13039/501100008530
                Award ID: SynMODEST
                Award ID: SynIsItFlutter
                Funded by: Deutsche Forschungsgemeinschaft 10.13039/501100001659
                Award ID: 314838170
                Award ID: GRK 2297 MathCoRe
                Funded by: International Max Planck Research School for Advanced Methods in Process and Systems Engineering 10.13039/501100012318
                Categories
                Physiology
                Original Research

                Anatomy & Physiology
                polycythemia vera,optimal control,modeling,numerical simulation,therapy scheduling,mixed-integer non-linear optimization,cancer,decision support

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