Now, however, researchers at The University of Texas M. D. Anderson Cancer Center are developing a risk assessment model that they hope will result in early detection of lung cancer in those smokers identified to be most at risk.
Using this prototype model, which is being discussed at the annual meeting of the American Association for Cancer Research (AACR), researchers already have calculated that a subset of heavy smokers who have emphysema and possess inefficient DNA repair capacity have as much as 11 times the risk of developing lung cancer.
"Our goal is to develop an instrument that can help physicians estimate risk for developing lung cancer, like the Gail model does for breast cancer, or the Framingham model used to predict heart disease," says the study's first author, Matthew Schabath, Ph.D., a postdoctoral researcher in the Department of Epidemiology.
The analysis is based on research that compared the medical history and DNA repair capacity profiles of 2,134 lung cancer patients treated at M. D. Anderson with the same data from 2,295 matched healthy individuals.
The prototype model is designed to first evaluate risk using only medical history, if that is all that is available, or a combination of medical history and genetic information related to molecular processes that either raise or reduce a person's risk of developing cancer. In this study, the researchers used a laboratory test that calculates how efficiently subjects' lymphocytes drawn into a test-tube repair damage from a tobacco carcinogen. In the future, more cost effective and simpler laboratory analyses need to be developed to represent the activity of genes involved in the repair processes.
Using the model, they have found, for example, that:
Allergies are believed to stimulate an immune response in lungs that help fight initial tumor development, Schabath says.
The model is a work in progress, says senior author Margaret Spitz, M.D., professor and chair of the Department of Epidemiology. "It appears to be reasonably accurate in that we can correctly classify over 78 percent of lung cancer cases," she says, adding that additional variables such as genetic variations in important pathways and more environmental risk factors will be added in the future.
"Early detection is key to successful treatment of any cancer, and this model is designed to help physicians identify and screen those patients most at risk for lung cancer," Spitz adds.
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