The contribution of risk prediction models to early detection of lung cancer

John K. Field*, Ying Chen, Michael W. Marcus, Fiona E. McRonald, Olaide Y. Raji, Stephen W. Duffy

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

19 Citations (Scopus)


Low-dose computed tomography screening is a strategy for early diagnosis of lung cancer. The success of such screening will be dependent upon identifying populations at sufficient risk in order to maximise the benefit-to-harm ratio of the intervention. To facilitate this, the lung cancer risk prediction community has established several risk models with good predictive performance. This review focuses on current progress in risk modelling for lung cancer prediction, with some views on future development. J. Surg. Oncol. 2013 108:304-311.

Original languageEnglish
Pages (from-to)304-311
Number of pages8
JournalJournal of Surgical Oncology
Issue number5
Publication statusPublished - Oct 2013
Externally publishedYes


  • early diagnosis
  • lung neoplasms
  • risk assessment
  • screening
  • statistical model

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