Lung cancer risk prediction nomogram for female non smokers

About 53% of lung cancers in females are not attributable to smoking worldwide and a new model presented at the IASLC World Conference on Lung Cancer may allow clinicians the ability to assess and stratify lung cancer risk in female non-smokers in China.

Lanwei Guo, & team examined data from 151,834 patients in China, from October 2013 to October 2019 from the Cancer Screening Program in Urban China.

The aim was to develop and validate a simple and non-invasive model which could assess and stratify lung cancer risk in female non-smokers in China.

Patients were randomly divided into the training (75,917) and validation (75,917) sets. Elder age, history of chronic respiratory disease, first-degree family history of lung cancer, menopause, and history of benign breast disease were the independent risk factors for lung cancer.

Using these five variables, Dr. Guo and colleagues plotted one-year, three-year, and five-year lung cancer risk prediction nomograms.

Related risk factors were identified through multivariable Cox regression analysis, followed by the establishment of a risk prediction nomogram. Discrimination [area under the curve (AUC)] and calibration were further performed to assess the validation of the risk prediction nomogram in the training set and then validated by the validation set.

"We developed and validated a simple and non-invasive lung cancer risk model in female non-smokers that can be applied to identify and triage patients at high risk for developing lung cancer in female non-smokers," Dr. Guo reported.

Ref:

Lanwei Guo et. al, MEETING, IASLC World Conference on Lung Cancer 2022, 9-Aug-2022