Selecting cases for whom additional tests can improve prognostication.

Conference Paper

Prognostic models are increasingly being used in clinical practice. The benefit of adding variables (e.g., gene expression measurements) to an original set of variables (e.g., phenotypes) when building prognostic models is usually measured on a whole set of cases. In practice, however, including additional information only helps build better models for some subsets of cases. It is important to prioritize who should undergo further testing. We present a method that can help identify those patients might benefit from additional testing. Our experiments based on limited breast cancer data indicate that relatively old patients with large tumors and positive lymph nodes constitute a group for whom prognoses can be more accurate with the addition of gene expression measurements. The same is not true for some other groups.

Full Text

Duke Authors

Cited Authors

  • Jiang, X; Kim, J; Wu, Y; Wang, S; Ohno-Machado, L

Published Date

  • 2012

Published In

Volume / Issue

  • 2012 /

Start / End Page

  • 1260 - 1268

PubMed ID

  • 23304404

Pubmed Central ID

  • PMC3540468

Electronic International Standard Serial Number (EISSN)

  • 1942-597X

Conference Location

  • United States