Primary lung cancer vs metastatic breast cancer: a probabilistic approach.

Published

Journal Article

In this study, a mathematical and probabilistic model is used to study the probability that a lung tumor is a primary vs a metastasis from cancer of the breast. The model uses information from immunohistochemical stains for thyroid transcription factor (TTF)-1, mammaglobin, p63, and estrogen receptor and epidemiologic data about primary lung and metastatic breast cancers in women. The results demonstrate that these 4 stains can yield nearly certain diagnoses in approximately 80% of tumors falling into the pool of this differential diagnosis. Nevertheless, uncertainty of diagnosis remains for the 19% of tumors in the pool that are negative for TTF-1, mammaglobin, and p63.

Full Text

Duke Authors

Cited Authors

  • Vollmer, RT

Published Date

  • September 2009

Published In

Volume / Issue

  • 132 / 3

Start / End Page

  • 391 - 395

PubMed ID

  • 19687315

Pubmed Central ID

  • 19687315

Electronic International Standard Serial Number (EISSN)

  • 1943-7722

Digital Object Identifier (DOI)

  • 10.1309/AJCPDIP12IUGVRQR

Language

  • eng

Conference Location

  • England