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

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 predic...

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Bibliographic Details
Published in:Journal of surgical oncology 2013-10, Vol.108 (5), p.304-311
Main Authors: Field, John K., Chen, Ying, Marcus, Michael W., Mcronald, Fiona E., Raji, Olaide Y., Duffy, Stephen W.
Format: Article
Language:English
Subjects:
Early Detection of Cancer
early diagnosis
Female
Humans
Lung cancer
lung neoplasms
Lung Neoplasms - diagnosis
Male
Models, Statistical
Risk
risk assessment
Risk Reduction Behavior
screening
statistical model
Tomography, X-Ray Computed
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Summary: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. © 2013 Wiley Periodicals, Inc.
ISSN:0022-4790
1096-9098
DOI:10.1002/jso.23384