The potential for using risk models in future lung cancer screening trials

Abstract

Computed tomography screening for early diagnosis of lung cancer is one of the more potentially useful strategies, aside from smoking cessation programmes, for reducing mortality and improving the current poor survival from this disease. The long-term success of lung cancer screening will be dependent upon identifying populations at sufficient risk in order to maximise the benefit-to-harm ratio of the intervention. Risk prediction models could potentially play a major role in the selection of high-risk individuals who would benefit most from screening intervention programmes for the early detection of lung cancer. Improvements of developed lung cancer risk prediction models (through incorporation of objective clinical factors and genetic and molecular biomarkers for precise and accurate estimation of risks), demonstration of their clinical usefulness in decision making, and their use in future screening programmes are the focus of current research.