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 language | English |
|---|---|
| Pages (from-to) | 1907-1913 |
| Number of pages | 7 |
| Journal | International Journal of Cancer |
| Volume | 129 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - 15 Oct 2011 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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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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