The development and execution of medical prediction models Book Section


Authors: Kattan, M. W.; Gonen, M.; Scardino, P. T.
Editors: Taktak, A. F. G.; Fisher, A. C.
Article/Chapter Title: The development and execution of medical prediction models
Abstract: Multivariable regression models are firmly established as the standard method in medical literature for obtaining adjusted estimates and adjusted tests of association. Prediction of individual patient outcome is a different area than testing for associations. The purpose of this chapter is to present the strategy developed by others that is used for building and implementing several regression-based prediction models. One of the software products is the most common prognostic tools in cancer for the personal digital assistant, according to a survey by the American Society of Clinical Oncology. One of the specific messages conveyed here is that building prediction models require a different strategy even though the statistical models are the same. This chapter emphasizes on achieving high predictive accuracy as the goal rather than building a model with statistically significant factors. It also reviews the importance of model validation and calibration as indispensable steps before finalizing a predictive model.It focuses on simple and effective communication of the results. The tool used for this purpose is the nomogram. This graphical depiction of a multivariable model has been used for a long time but not as widely as one might expect, given its advantages. © 2007 Elsevier B.V. All rights reserved.
Book Title: Outcome Prediction in Cancer
ISBN: 978-0-444-52855-1
Publisher: Elsevier Inc.  
Publication Place: Amsterdam, Netherlands
Date Published: 2007-01-01
Start Page: 443
End Page: 455
Language: English
DOI: 10.1016/B978-044452855-1/50018-0
PROVIDER: scopus
DOI/URL:
Notes: --- - Book Chapter 16 - 9780444528551 (ISBN) - "Export Date: 1 October 2013" - "Source: Scopus"
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  1. Peter T Scardino
    648 Scardino
  2. Mithat Gonen
    832 Gonen