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Risk prediction model may help determine if a lung nodule will progress to cancer

By 8th August 2019No Comments

A risk prediction model has been developed using clinical and radiological features that could stratify individuals presenting with a lung nodule as having high or low risk for lung cancer (Nemesure B. Will That Pulmonary Nodule Become Cancerous? A Risk Prediction Model for Incident Lung Cancer. Cancer Prev Res (Phila). 2019 Jun 27. doi: 10.1158/1940-6207.CAPR-18-0500).

Lung cancer is often asymptomatic in early stages, and the identification of high-risk individuals is a major priority,” said lead author Dr. B Nemesure and colleagues analyzed data from 2,924 patients presenting with a lung nodule . Patients were excluded if they had a history of lung cancer or if they were diagnosed with lung cancer within six months of the initial consultation. Participants were randomly assigned to discovery (1,469 patients) and replication (1,455 patients) cohorts. Among them, 171 developed lung cancer over the 13-year period.

Clinical and radiological data were collected to develop a risk prediction model. Using multivariable analyses, the researchers found that the combined variables of age, smoking pack-years, personal history of cancer, the presence of COPD, and nodule characteristics such as size, spiculation, and ground-glass opacity, could best predict who would develop lung cancer. These factors were combined to develop an overall risk score to stratify patients into high- and low-risk categories.

When the risk score was applied to the replication cohort, the researchers found that the model could discriminate cancer risk with a sensitivity and specificity of 73 percent and 81 percent, respectively. Compared with individuals in the low-risk category, those in the high-risk category had more than 14 times the risk of developing lung cancer.

The authors commented: “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”.

doi: 10.1158/1940-6207.CAPR-18-050)0.