Researchers have developed a new risk prediction model that may better identify which patients with lung nodules could develop lung cancer.
“Lung cancer is often asymptomatic in early stages, and the identification of high-risk individuals is a major priority. While lung nodules are not uncommon, a major challenge in the field is determining which nodules will progress to cancer,” said lead author Barbara Nemesure, PhD, director, Cancer Prevention and Control Program and the Lung Cancer Program, Stony Brook Cancer Center, Stony Brook, NY.
In their study, recently published in Cancer Prevention Research, Dr. Nemesure and colleagues sought to prospectively predict the incidence of lung cancer among people in a general population who presented with a lung nodule. They analyzed data from 2,924 patients referred to the Stony Brook Cancer Center’s Lung Cancer Evaluation Center for evaluation of a pulmonary nodule, excluding those who had a history of lung cancer and those diagnosed with lung cancer within the past 6 months. They randomized patients to a discovery cohort (n=1,469) and a replication cohort (n=1,455).
Over the 13-year study period, 171 patients developed lung cancer.
To develop their risk prediction model, Dr. Nemesure and fellow researchers collected patients’ clinical and radiologic data. Upon multivariate analyses, they found that combining age, pack-years of smoking, personal history of cancer, the presence of chronic obstructive pulmonary disease, and nodule characteristics including size, speculation, and ground-glass opacity, they could best predict which of the patients in the discovery cohort would develop cancer.
These factors were combined to form an overall risk score, with which patients could be stratified into low- or high-risk categories.
The researchers then applied this risk score to patients in the replication cohort, and found that it determined cancer risk with a sensitivity of 73% and a specificity of 81%. In patients categorized as high risk using the model, the risk of developing lung cancer was 14 times greater than that in those categorized as low risk.
“Even though the majority of lung nodules do not progress to cancer, it is still vitally important that patients seek follow-up care,” said Dr. Nemesure. “Through our model, we can identify which individuals with lung nodules should be closely monitored, so that we can catch the disease at an early stage and ultimately reduce the burden of lung cancer deaths.”
Ultimately, the discovery of such risk models, especially to predict the probability of patients developing cancer, will help with early detection and management and lead to better outcomes.
“Quantification of reliable risk scores has a high clinical utility, enabling physicians to better stratify treatment protocols to manage patient care. The final model is among the first tools developed to predict incident lung cancer in patients presenting with a concerning pulmonary nodule,” concluded Dr. Nemesure and her colleagues.
This study was supported by the Stony Brook Cancer Center.