Skip to main content
Log in

Stochastic Trees and the StoTree Modeling Environment: Models and Software for Medical Decision Analysis

  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

In this paper we present a review of stochastic trees, a convenient modeling approach for medical treatment decision analyses. Stochastic trees are a generalization of decision trees that incorporate useful features from continuous-time Markov chains. We also discuss StoTree, a freely available software tool for the formulation and solution of stochastic trees, implemented in the Excel spreadsheet environment.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

REFERENCES

  1. Hazen, G. B., Stochastic trees: A new technique for temporal medical decision modeling. Med. Decis. Making 12:163-178, 1992.

    Google Scholar 

  2. Hazen, G. B., Factored stochastic trees: A tool for solving complex temporal medical decision models. Med. Decis. Making 13:227-236, 1993.

    Google Scholar 

  3. Beck, J. R., and Pauker, S. G., The Markov process in medical prognosis. Med. Decis. Making 3:419-458, 1983.

    Google Scholar 

  4. Sonnenberg, F. A., and Beck, J. R., Markov models in medical decision making: A practical guide. Med. Decis. Making 13:322-338, 1993.

    Google Scholar 

  5. Beck, J. R., Kassirer, J. P., and Pauker, S. G., A convenient approximation of life expectancy (the “DEALE”). I: Validation of the method. Am. J. Med. 73:883-888, 1982.

    Google Scholar 

  6. Hollenberg, J. P., Markov cycle trees:Anew representation for complex Markov processes (Abstract). Med. Decis. Making 4:529, 1984.

    Google Scholar 

  7. Matchar, D. B., and Pauker, S. G., Transient ischemic attacks in a man with coronary artery disease: Two strategies neck and neck. Med. Decis. Making 6:239-249, 1986.

    Google Scholar 

  8. Hazen, G. B., Morrow, M., and Venta, E. R., Patient Values in the Treatment of Ductal Carcinoma in Situ. In Society for Medical Decision Making Annual Meeting, Reno, NV, October 1999.

  9. Silverstein, M. J., Cohen, B. F., Gierson, E.D., Furmanski, M., Gamagami, P., Colburn, W. J., Lewinsky, B. S., and Waisman, J. R., Duct carcinoma in situ: 227 cases without microinvasion. Eur. J. Cancer 28: 630-634, 1992.

    Google Scholar 

  10. Hiramatsu, H., Bornstein, B. A., Recht, A., Schnitt, S. J., Baum, J. K., Connolly, J. L., Duda, R. B., Guidi, A. J., Kaelin, C. M., Silver, B., and Harris, J. R., Local recurrence after conservative surgery and radiation therapy for ductal carcinoma in situ. Cancer J. Sci. Am. 1:55-61, 1995.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hazen, G.B. Stochastic Trees and the StoTree Modeling Environment: Models and Software for Medical Decision Analysis. Journal of Medical Systems 26, 399–413 (2002). https://doi.org/10.1023/A:1016401115823

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1016401115823

Navigation