A new "clinicogenomic model" has been developed by researchers at the Boston University School of Medicine to accurately test for lung cancer.
The research team says that the model combines a specific gene expression for lung cancer as well as clinical risk factors.
An earlier study by the same researchers reported a gene expression biomarker capable of distinguishing cytologically normal large airway epithelial cells from smokers with and without lung cancer.
However, the biomarker has limited sensitivity depending on the stage and the location of the cancer.
For the current study, the researchers looked at the present and former smokers undergoing bronchoscopies for suspicion of lung cancer and compared the likelihood of the subjects having lung cancer using the biomarker, the clinical risk factors and a combination of the two -- clinicogenomic model.
They found patients using the clinicogenomic model had increased sensitivity, specificity, positive value and negative predictive value of their cancer compared to the other methods.
"Our data suggests that the clinicogenomic model might serve to identify patients who would benefit from further invasive testing, thereby expediting the diagnosis and treatment for their malignancy," said senior author Avrum Spira, MD, an assistant professor of medicine and pathology at Boston University School of Medicine.
According to the researchers, it is hoped this prediction model will speed up more invasive testing and appropriate therapies for smokers with lung cancer as well as decrease invasive diagnostic procedures for individuals without lung cancer.
Lung cancer is the leading cause of cancer death in the world, with more than one million deaths worldwide annually.
The study currently appears on-line in the journal Cancer Prevention Research.