Lung cancer is the most common cause of cancer death in the UK. Two-thirds of patients are diagnosed at an advanced stage which is much harder to treat as the cancer has already spread. If lung cancer is diagnosed at an earlier stage, the chances of successful treatment and survival are much higher.
A high platelet count is a risk marker for undiagnosed cancer in primary care. We have recently found that the platelet count begins to rise 6 months before a lung cancer diagnosis which highlights a potential to accelerate lung cancer diagnoses. Levels of other blood markers that are taken alongside platelet count are also altered in lung cancer patients.
In this PhD, Melissa will develop a statistical model that uses platelet count, other blood markers that are taken alongside platelet count, smoking status and age (other risk factors for lung cancer) to estimate a patient’s risk of lung cancer and to help identify which patients may benefit from lung cancer investigations. This model can help to detect lung cancer sooner, increase the chances of being diagnosed at an early stage, and increase survival rates.
We aim to develop and validate this model using existing primary care data from both the UK Biobank and the Clinical Practice Research Datalink to ensure our model performs well in UK primary care.