IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v56y2012i6p1723-1736.html
   My bibliography  Save this article

Inference on a stochastic two-compartment model in tumor growth

Author

Listed:
  • Albano, Giuseppina
  • Giorno, Virginia
  • Román-Román, Patricia
  • Torres-Ruiz, Francisco

Abstract

A continuous-time model that incorporates several key elements in tumor dynamics is analyzed. More precisely, the form of proliferating and quiescent cell lines comes out from their relations with the whole tumor mass, giving rise to a two-dimensional diffusion process, generally time non-homogeneous. This model is able to include the effects of the mutual interactions between the two subpopulations. Estimation of the rates of the two subpopulations based on some characteristics of the involved diffusion processes is discussed when longitudinal data are available. To this aim, two procedures are presented. Some simulation results are developed in order to show the validity of these procedures as well as to compare them. An application to real data is finally presented.

Suggested Citation

  • Albano, Giuseppina & Giorno, Virginia & Román-Román, Patricia & Torres-Ruiz, Francisco, 2012. "Inference on a stochastic two-compartment model in tumor growth," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1723-1736.
    • Handle: RePEc:eee:csdana:v:56:y:2012:i:6:p:1723-1736
    DOI: 10.1016/j.csda.2011.10.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167947311003732
    Download Restriction: Full text for ScienceDirect subscribers only.
    File URL: https://libkey.io/10.1016/j.csda.2011.10.016?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Castorina, Paolo & Zappalà, Dario, 2006. "Tumor Gompertzian growth by cellular energetic balance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 365(2), pages 473-480.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Virginia Giorno & Amelia G. Nobile, 2019. "Restricted Gompertz-Type Diffusion Processes with Periodic Regulation Functions," Mathematics, MDPI, vol. 7(6), pages 1-19, June.
    2. Albano, G. & Giorno, V., 2020. "Inferring time non-homogeneous Ornstein Uhlenbeck type stochastic process," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).
    3. Giorno, Virginia & Román-Román, Patricia & Spina, Serena & Torres-Ruiz, Francisco, 2017. "Estimating a non-homogeneous Gompertz process with jumps as model of tumor dynamics," Computational Statistics & Data Analysis, Elsevier, vol. 107(C), pages 18-31.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Llanos-Pérez, J.A. & Betancourt-Mar, J.A. & Cocho, G. & Mansilla, R. & Nieto-Villar, José Manuel, 2016. "Phase transitions in tumor growth: III vascular and metastasis behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 560-568.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:56:y:2012:i:6:p:1723-1736. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/csda .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.