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On Consolidated Predictive Model of the Natural History of Breast Cancer: Primary Tumor and Secondary Metastases in Patients with Lymph Nodes Metastases

Published: 02 July 2017 Publication History

Abstract

This paper is devoted to mathematical modelling of the progression and stages of breast cancer. The "Consolidated mathematical growth Model of primary tumor (PT) and secondary distant metastases (MTS) in patients with lymph nodes MTS (Stage III)" (CoM-III) is proposed as a new research tool. The CoM-III rests on an exponential tumor growth model and consists of a system of determinate nonlinear and linear equations. The CoM-III describes correctly primary tumor growth (parameter T) and distant metastases growth (parameter M, parameter N). The CoM-III model and predictive software: a) detect different growth periods of primary tumor and distant metastases in patients with lymph nodes MTS; b) make forecast of the period of the distant metastases appearance in patients with lymph nodes MTS; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of breast cancer and facilitate optimisation of diagnostic tests. The CoM-III enables us, for the first time, to predict the it whole natural history of PT and secondary distant MTS growth of patients with/without lymph nodes MTS on each stage relying only on PT sizes.

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  1. On Consolidated Predictive Model of the Natural History of Breast Cancer: Primary Tumor and Secondary Metastases in Patients with Lymph Nodes Metastases

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        cover image ACM Other conferences
        DH '17: Proceedings of the 2017 International Conference on Digital Health
        July 2017
        256 pages
        ISBN:9781450352499
        DOI:10.1145/3079452
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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        Published: 02 July 2017

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        Author Tags

        1. breast cancer
        2. exponential model
        3. lymph nodes metastases
        4. mathematical modelling
        5. predictor
        6. primary tumor
        7. secondary metastases
        8. survival

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        DH '17: International Conference on Digital Health
        July 2 - 5, 2017
        London, United Kingdom

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