Brock lung cancer prediction model leads to more years of life saved than U.S. screening method

A lung cancer prediction model developed by a Brock University epidemiologist is more efficient in selecting people to undergo lung cancer screening than the method used in the United States, says research published this month in Lancet Oncology.

Professor Emeritus of Health Sciences Martin Tammemägi was one of the leaders of the International Lung Screening Trial that compared the model he created a decade ago — PLCOm2012 — to the United States Preventative Services Task Force’s model, USPSTF2013.

The research team recruited 5,819 individuals for low-dose computed tomography (CT) lung cancer screening at nine sites in Canada, Australia, the U.K. and Hong Kong.

Individuals were enrolled for screening using Tammemägi’s PLCOm2012 model criteria or the United States Preventive Services Task Force criteria.

“The PLCOm2012 model criteria led to the detection of 16 per cent more lung cancers than the U.S. Preventative Services Task Force’s criteria, and to significantly more cumulative life years potentially gained by those diagnosed with lung cancer,” says Tammemägi.

CT lung cancer screening detects earlier stages of cancer, which are often cured by surgery. Without screening, most lung cancers are discovered at an advanced stage, with most cases being fatal.

Since lung cancer is the leading cause of cancer death in North America and the world, it’s vital that high-risk individuals be identified early for screening, says Tammemägi. Lung cancer screening can reduce lung cancer deaths by 20 per cent or more.

Key to Tammemägi’s model’s success is that it contains more factors that more accurately estimate lung cancer risk and determine who is eligible for CT scanning.

“In comparison, the U.S. Preventive Services Task Force criteria are simplistic and narrow,” he says. Besides being widely used in the United States, other countries such as South Korea are following the United States Preventative Services Task Force’s eligibility criteria.

The United States model’s criteria are based on age, pack-years and quit years in former smokers. A pack-year is smoking one package a day for one year or its equivalent, for example, smoking a half-pack a day for two years equals one pack-year.

In contrast, Tammemägi’s model uses 11 factors including the number of cigarettes smoked per day, the number of years of smoking, race/ethnicity, age, highest level of education obtained, family history of lung cancer, body mass index, among others — and these predictors are included in mathematical equations to estimate the risk of an individual getting lung cancer over time.

As a result, “more at-risk people can get screening that could save their lives, and fewer low-risk individuals who won’t get lung cancer are subjected to needless harms of screening,” he says.

Tammemägi’s PLCOm2012 model has been widely validated and is being used now for selecting individuals for screening in the Ontario Lung Screening Program and in the United Kingdom National Health Services (NHS) Lung Health Check Program. It is also planned for use in lung cancer screening in programs or pilots in British Columbia, Quebec, Australia and New Zealand.

In separate but related research, Tammemägi is one of three co-lead investigators in a U.S. National Institutes of Health, National Cancer Institute-funded study investigating whether a panel of protein biomarkers circulating in the blood together with the PLCOm2012 model risk estimates can better identify people for CT lung cancer screening.

The team’s research, published this month in the Journal of Clinical Oncology, found that adding the results of a four biomarker panel of prosurfactant protein B, cancer antigen 125, carcinoembryonic antigen and cytokeritan-19 to the PLCOm2012 model significantly improved prediction of future lung cancer.

“The study was very successful,” says Tammemägi. “This is an important finding, because it now lets us identify who should get lung cancer screening with even greater accuracy.

“The results of the combined biomarker and PLCOm2012 evaluations can provide patients and doctors with strong evidence on which to base decisions regarding performing and continuing to perform lung cancer screening,” says Tammemägi.

The PLCOm2012 model and associated risk calculators are posted on Brock’s Lung Cancer Risk Calculators website. Tammemägi says he and his team are working on expanding the PLCOm2012 model.

Tammemägi is the Scientific Lead for Ontario Health – Cancer Care Ontario’s Ontario Lung Screening Program. Many other Canadian provinces are now following Ontario’s example.

Read more stories in: Applied Health Sciences, Faculty & staff, Featured, News, Research
Tagged with: , , , , , , , , , ,