Principal Investigator: Dr David Muller
Department: International Agency for Research on Cancer, Genetic Epidemiology Group
International Agency for Research on Cancer, Genetic Epidemiology Group,
150 Cours Albert Thomas, Lyon, 69008 France
Lung cancer is the most commonly diagnosed cancer in the world. Overall,
survival from lung cancer is low, but there is substantial variability in survival
rates by stage at presentation. This suggests that screening for lung cancer
might be beneficial in order to identify tumours earlier, when the potential for
effective treatment is greatest. While screening for lung cancer could possibly
provide a benefit in terms of reducing mortality, there is also the potential for
harm and needless expense in following up false positives detected by the
screening program. Thus, any screening program must target individuals at
high risk of lung cancer in order to maximise its potential benefits, while
minimising potential harm.
Numerous statistical models have been developed for the purposes of
predicting individual risk of lung cancer based on characteristics such as
tobacco use, family history of lung cancer, and prior diagnosis of lung diseases
(see references in section 2). Before these models can be used to inform
screening guidelines, they must be externally validated and calibrated. That is,
the models must be able to discriminate between those at high and low risk of
lung cancer, and must provide accurate estimates of absolute risk when
applied to different populations.
We propose to compare the performance of several established lung cancer
risk prediction models using data from UK Biobank. In addition, we aim to
assess whether measures of lung function, such as the forced expiratory
volume in one second, might improve the discriminatory power of lung cancer
risk prediction models. These models will be applied to all UK Biobank
participants for whom spirometry data are available. In addition to spirometry
data, this research requires questionnaire data and incident cancer diagnoses.
No biological specimens are required. This proposal is consistent with UK
Biobank’s mission of health-related research in the public interest.