Advanced Search

Methods of Model Calibration: Observations from a Mathematical Model of Cervical Cancer

Contents:

Author Info

  • Douglas C.A. Taylor

    (i3 Innovus, Medford, Massachusetts, USA)

  • Vivek Pawar

    (i3 Innovus, Medford, Massachusetts, USA)

  • Denise Kruzikas

    (Lovelace Respiratory Research Institute, Kannapolis, North Carolina, USA)

  • Kristen E. Gilmore

    (i3 Innovus, Medford, Massachusetts, USA)

  • Ankur Pandya

    (Harvard School of Public Health, Boston, Massachusetts, USA)

  • Rowan Iskandar

    (University of Minnesota, Minneapolis, Minnesota, USA)

  • Milton C. Weinstein

    (i3 Innovus, Medford, Massachusetts, USA; Harvard School of Public Health, Boston, Massachusetts, USA)

Registered author(s):

    Abstract

    Background: Mathematical models are commonly used to predict future benefits of new therapies or interventions in the healthcare setting. The reliability of model results is greatly dependent on accuracy of model inputs but on occasion, data sources may not provide all the required inputs. Therefore, calibration of model inputs to epidemiological endpoints informed by existing data can be a useful tool to ensure credibility of the results. Objective: To compare different computational methods of calibrating a Markov model to US data. Methods: We developed a Markov model that simulates the natural history of human papillomavirus (HPV) infection and subsequent cervical disease in the US. Because the model consists of numerous transition probabilities that cannot be directly estimated from data, calibration to multiple disease endpoints was required to ensure its predictive validity. Goodness of fit was measured as the mean percentage deviation of model-predicted endpoints from target estimates. During the calibration process we used the manual, random and Nelder-Mead calibration methods. Results: The Nelder-Mead and manual calibration methods achieved the best fit, with mean deviations of 7% and 10%, respectively. Nelder-Mead accomplished this result with substantially less analyst time than the manual method, but required more intensive computing capability. The random search method achieved a mean deviation of 39%, which we considered unacceptable despite the ease of implementation of that method. Conclusions: The Nelder-Mead and manual techniques may be preferable calibration methods based on both performance and efficiency, provided that sufficient resources are available.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://PharmacoEconomics.adisonline.com/pt/re/pec/pdfhandler.00019053-201028110-00004.pdf
    Download Restriction: Pay per view
    File URL: http://PharmacoEconomics.adisonline.com/pt/re/pec/fulltext.00019053-201028110-00004.htm
    Download Restriction: Pay per view

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Bibliographic Info

    Article provided by Springer Healthcare | Adis in its journal PharmacoEconomics.

    Volume (Year): 28 (2010)
    Issue (Month): 11 ()
    Pages: 995-1000
    Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
    Handle: RePEc:wkh:phecon:v:28:y:2010:i:11:p:995-1000

    Contact details of provider:
    Web page: http://pharmacoeconomics.adisonline.com/

    For corrections or technical questions regarding this item, or to correct its listing, contact: (Dave Dustin).

    Related research

    Keywords: cervical-cancer; human-papillomavirus-infections; treatment; modelling.;

    Find related papers by JEL classification:

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:wkh:phecon:v:28:y:2010:i:11:p:995-1000

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dave Dustin).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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