A computer risk-prediction model assessing a patient's risk for developing lung cancer proved more accurate than assessments based on smoking duration or family history, a new research study finds.
The Liverpool Lung Project risk model was used to determine whether patients should be referred for CT scans to screen for early signs of cancer, according to the study, published today in the Annals of Internal Medicine. The model attempts to predict the five-year risk for lung cancer.
The risk-assessment model was tested against three other studies, including Harvard University case-control studies and the European Early Lung Cancer project. The results were deemed "good" in two cases, with "modest discrimination" achieved in the third. It is unclear whether including other risk factors such as genetic markets would improve the accuracy of the tool, the researchers say.
The risk-assessment tool evaluated five categories to identify high-risk patients, reports MedPage Today: history of pneumonia and other types of cancer, exposure to asbestos, family history of lung cancer and how long the patient had smoked.
The model was developed by researchers at the University of Liverpool's Cancer Research Center, according to the research announcement, which notes the tool can be used to identify patients who could benefit from prevention and control programs, as well as for early diagnosis of cancer.