Locally developed lung cancer classification tool

Issue: BCMJ, vol. 55 , No. 8 , October 2013 , Pages 365-366 News

A study led by the Terry Fox Research Institute (TFRI) has led to the development of a new clinical risk calculator software that accurately classifies, 9 out of 10 times, which spots or lesions are benign and which are malignant on an initial lung CT scan among individuals at high risk for lung cancer. 

The population-based study, published in the NEJM, examined 12029 lung cancer nodules observed on CTs of 2961 current and former smokers. The findings are expected to have a worldwide clinical impact on the diagnosing and treatment of individuals with lung cancer, and provide new evidence for developing and improving lung-cancer screening programs. 

The study’s co-principal investigator is Dr Stephen Lam, chair of BC’s Provincial Lung Tumour Group at the BC Cancer Agency and a professor of medicine at the University of British Columbia. Dr Lam says that the new risk cal-culator can accurately predict which abnormalities showing up on a first CT require further follow-up, such as a repeat CT scan, a biopsy, or surgery, and which ones do not. 

According to Dr Lam, the new prediction model holds up even in cases where clinicians are faced with difficult challenges like deciding what to do when nodules are the approximate size of a blueberry, or smaller. While nodule size is one predictor of lung cancer, the largest nodule appearing on the CT was not necessarily cancerous. The study team found that nodules located in the upper lobes of the lung carry an increased probability of cancer, and that where cancer was present, fewer nodules were found. The new model will simplify the work involved in evaluating and assessing nodules on scans for radiologists, respirologists, and thoracic surgeons who make decisions about tests and treatment for their patients. 

The study, entitled “Probability of Cancer in Pulmonary Nodules Detected on First Screening CT,” can be viewed at www.nejm.org/doi/full/10.1056/NEJMoa1214726.

. Locally developed lung cancer classification tool. BCMJ, Vol. 55, No. 8, October, 2013, Page(s) 365-366 - News.

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