IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v26y2006i2p134-144.html
   My bibliography  Save this article

Apparent and Internal Validity of a Monte Carlo–Markov Model for Cardiovascular Disease in a Cohort Follow-up Study

Author

Listed:
  • Rogier L. Nijhuis
  • Theo Stijnen

    (Department of Epidemiology and Biostatistics, Erasmus Medical Center, Rotterdam, the Netherlands)

  • Anna Peeters

    (Department of Public Health, Erasmus Medical Center, Rotterdam, the Netherlands)

  • Jacqueline C.M. Witteman
  • Albert Hofman

    (Department of Epidemiology and Biostatistics, Erasmus Medical Center, Rotterdam, the Netherlands)

  • M. G. Myriam Hunink

    (Department of Radiology, Erasmus Medical Center, Rotterdam, the Netherlands; Departments of Health Policy & Management, Harvard School of Public Health, Boston, MA; Dept. of Epidemiology & Biostatistics, Erasmus Medical Center Rotterdam, P.O. Box 1738, 3000 DR Rotterdam, the Netherlands; phone: +31 10 408 7391; fax: +31 10 408 9382 m.hunink@erasmusmc.nl)

Abstract

Objective . To determine the apparent and internal validity of the Rotterdam Ischemic heart disease & Stroke Computer (RISC) model, a Monte Carlo–Markov model, designed to evaluate the impact of cardiovascular disease (CVD) risk factors and their modification on life expectancy (LE) and cardiovascular disease–free LE (DFLE) in a general population (hereinafter, these will be referred to together as (DF)LE). Methods. The model is based on data from the Rotterdam Study, a cohort follow-up study of 6871 subjects aged 55 years and older who visited the research center for risk factor assessment at baseline (1990–1993) and completed a follow-up visit 7 years later (original cohort). The transition probabilities and risk factor trends used in the RISC model were based on data from 3501 subjects (the study cohort). To validate the RISC model, the number of simulated CVD events during 7 years’ follow-up were compared with the observed number of events in the study cohort and the original cohort, respectively, and simulated (DF)LEs were compared with the (DF)LEs calculated from multistate life tables. Results .Both in the study cohort and in the original cohort, the simulated distribution of CVD events was consistent with the observed number of events (CVD deaths: 7.1% v. 6.6% and 7.4% v. 7.6%, respectively; non-CVD deaths: 11.2% v. 11.5% and 12.9% v. 13.0%, respectively). The distribution of (DF)LEs estimated with the RISC model consistently encompassed the (DF)LEs calculated with multistate life tables. Conclusions. The simulated events and (DF)LE estimates from the RISC model are consistent with observed data from a cohort follow-up study

Suggested Citation

  • Rogier L. Nijhuis & Theo Stijnen & Anna Peeters & Jacqueline C.M. Witteman & Albert Hofman & M. G. Myriam Hunink, 2006. "Apparent and Internal Validity of a Monte Carlo–Markov Model for Cardiovascular Disease in a Cohort Follow-up Study," Medical Decision Making, , vol. 26(2), pages 134-144, March.
    • Handle: RePEc:sae:medema:v:26:y:2006:i:2:p:134-144
    DOI: 10.1177/0272989X05284103
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X05284103
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X05284103?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
    ---><---

    Citations

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


    Cited by:

    1. Xudong Du & Mier Li & Ping Zhu & Ju Wang & Lisha Hou & Jijie Li & Hongdao Meng & Muke Zhou & Cairong Zhu, 2018. "Comparison of the flexible parametric survival model and Cox model in estimating Markov transition probabilities using real-world data," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-13, August.
    2. Daniel F. Otero-Leon & Mariel S. Lavieri & Brian T. Denton & Jeremy Sussman & Rodney A. Hayward, 2023. "Monitoring policy in the context of preventive treatment of cardiovascular disease," Health Care Management Science, Springer, vol. 26(1), pages 93-116, March.

    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:sae:medema:v:26:y:2006:i:2:p:134-144. 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: SAGE Publications (email available below). General contact details of provider: .

    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.