In this latest project, Tammem\u00e4gi, along with the University of British Columbia\u2019s Trevor Drummer, will extend the previous research to non-smokers.<\/p>\n
\u201cThe proportion of lung cancers in individuals who never smoked is growing and in some parts of the world outnumber lung cancer in individuals who smoked,\u201d he says. \u201cLung cancer in individuals who never smoked when considered as a separate group is the seventh leading cause of cancer deaths.\u201d<\/strong><\/p>\n In the lung prediction model for individuals who smoked, individuals are assessed using 11 factors, including the average number of cigarettes smoked per day, the number of years of smoking, whether they currently smoke, race\/ethnicity, age, highest level of education obtained, family history of lung cancer, personal history of cancer and lung disease, and body mass index.<\/p>\n Martin Tammem\u00e4gi, Brock University Professor Emeritus of Epidemiology.<\/p><\/div>\n These predictors are included in mathematical equations<\/a> to estimate the risk of an individual getting lung cancer over time.<\/p>\n The new model will eliminate the criteria related to smoking and instead will include exposure to a class of airborne pollutants known as particulate matter or \u2018PM2.5<\/sub><\/a> \u2018, which are tiny particles of soot, elemental and organic carbon, among other things. The impact of nitrogen dioxide and ozone will also be evaluated.<\/p>\n \u201cAir pollution may lead to cancer by causing inflammation and oxidative stress of lung tissue and by inactivating cancer controlling genes,\u201d says Tammem\u00e4gi.<\/p>\n He says scientists study cumulative exposure to air pollution by linking individuals\u2019 residential addresses to satellite image estimates of different air pollutants.<\/p>\n \u201cBecause historical records of such data have been stored, we can look back over 20 years to summarize cumulative air pollution exposures,\u201d says Tammem\u00e4gi.<\/p>\n To construct the new model, he and his team will be using patient data from studies produced by a variety of research groups in Canada, the U.K., Taiwan and the U.S.<\/p>\n As in the case of the model for individuals who smoked, the purpose of the lung cancer prediction model for individuals who did not smoke is to identify individuals who are at high risk for cancer so that they can be offered and benefit from lung cancer screening.<\/p>\n Low-dose computed tomography (CT) lung cancer screening for high-risk individuals detects earlier stages of cancer, which are often cured by surgery. Without screening, most lung cancers are detected at advanced stages, with most cases having poor survival.<\/p>\n Tammem\u00e4gi says CT lung cancer screening has been shown to reduce lung cancer mortality by more than 20 per cent in high-risk individuals.<\/p>\n In Canada, lung cancer is the leading cause of cancer death, according to government statistics<\/a>, with survival for lung cancer among the lowest of all types of cancer.<\/p>\n![\"Martin](\"https:\/\/brocku.ca\/brock-news\/wp-content\/uploads\/2023\/09\/MartinTammagi2-1050x748.jpeg\")