Abstract
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 language | English |
|---|---|
| Pages (from-to) | 304-311 |
| Number of pages | 8 |
| Journal | Journal of Surgical Oncology |
| Volume | 108 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - Oct 2013 |
| Externally published | Yes |
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
- early diagnosis
- lung neoplasms
- risk assessment
- screening
- statistical model
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