Estimating individual risk for lung cancer Academic Article uri icon

Overview

MeSH Major

  • Lung Neoplasms
  • Models, Statistical
  • Smoking

abstract

  • Lung cancer risk prediction models hold the promise of improving patient care and streamlining research. The ultimate goal of these models is to inform clinicians as to which interventions their individual patients should receive to reduce lung cancer-associated morbidity and mortality. In this paper, we discuss the history and current state of lung cancer prediction models, focusing on three models: the Bach model, the Spitz model, and the Liverpool Lung Project (LLP) model. We also discuss the prospects for further development of improved prediction models for lung cancer risk. Although current models can identify those smokers at highest risk for lung cancer, these models are presently of limited use in the clinical setting. Nevertheless, lung cancer risk prediction models can be used during study enrollment to select more appropriate study subjects, and may eventually be useful in identifying patients for lung cancer screening or to receive chemoprevention.

publication date

  • April 22, 2011

Research

keywords

  • Academic Article

Identity

Language

  • eng

Digital Object Identifier (DOI)

  • 10.1055/s-0031-1272864

PubMed ID

  • 21500119

Additional Document Info

start page

  • 3

end page

  • 9

volume

  • 32

number

  • 1