IDEAS home Printed from https://ideas.repec.org/a/taf/tjsmxx/v12y2018i4p283-294.html
   My bibliography  Save this article

A system dynamics-based decision support model for chemotherapy planning

Author

Listed:
  • M. Heshmat
  • A. Eltawil

Abstract

This paper introduces a system dynamics model to address the effectiveness of chemotherapy treatment plan. This model includes all the treatment process variables which have been considered in the literature; moreover, we propose new variables such as the impairment caused by both the tumor growth and the adverse effect of chemotherapy doses, and the treatment efficacy which is the response achievable from applying a chemotherapy protocol. Compared to previous works, the results exhibit reasonable decreasing values for the number of cancerous cells and toxicity levels with time. By conducting a sensitivity analysis for the model parameters, the results show that the model is stable and robust for accommodating different values of the parameters. We apply the model on a real chemotherapy protocol for lymphoma, and the proposed model gives a good accommodation of that protocol. A what-if analysis is conducted to the approved chemotherapy protocol via the developed simulation model to check dose cancellation and delay. The results show that the model is sensitive to both dose cancellation and delay, and gives implications about their bad effect on the treatment efficacy.

Suggested Citation

  • M. Heshmat & A. Eltawil, 2018. "A system dynamics-based decision support model for chemotherapy planning," Journal of Simulation, Taylor & Francis Journals, vol. 12(4), pages 283-294, October.
  • Handle: RePEc:taf:tjsmxx:v:12:y:2018:i:4:p:283-294
    DOI: 10.1057/s41273-017-0059-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1057/s41273-017-0059-8
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41273-017-0059-8?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.

    Citations

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


    Cited by:

    1. Majed Hadid & Adel Elomri & Regina Padmanabhan & Laoucine Kerbache & Oualid Jouini & Abdelfatteh El Omri & Amir Nounou & Anas Hamad, 2022. "Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling," IJERPH, MDPI, vol. 19(23), pages 1-34, November.

    More about this item

    Statistics

    Access and download statistics

    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:taf:tjsmxx:v:12:y:2018:i:4:p:283-294. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/tjsm .

    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.