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A smoking-based carcinogenesis model for lung cancer risk prediction

  • Millennia Foy
  • , Margaret R. Spitz
  • , Marek Kimmel
  • , Olga Y. Gorlova
  • University of Texas Health Science Center at Houston
  • University of Texas MD Anderson Cancer Center
  • Rice University

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

Lung cancer is the leading cancer killer for both men and women worldwide. Over 80% of lung cancers are attributed to smoking. In this analysis, the authors propose to use a two-stage clonal expansion (TSCE) model to predict an individual's lung cancer risk based on gender and smoking history. The TSCE model is traditionally fitted to prospective cohort data. Here, the authors describe a new method that allows for the reconstruction of cohort data from the combination of risk factor data obtained from a case-control study, and tabled incidence/mortality rate data, and discuss alternative approaches. The method is applied to fit a TSCE model based on smoking. The fitted model is validated against independent data from the control arm of a lung cancer chemoprevention trial, CARET, where it accurately predicted the number of lung cancer deaths observed.

Original languageEnglish
Pages (from-to)1907-1913
Number of pages7
JournalInternational Journal of Cancer
Volume129
Issue number8
DOIs
Publication statusPublished - 15 Oct 2011

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • TSCE model
  • lung cancer
  • risk prediction
  • smoking

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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