Simple Web Tool Can Predict Lung Cancer Risk in Long-Time Smokers (2003)

The 10-year risk of developing lung cancer in long-time smokers can be accurately predicted based on a just a few factors, including age, smoking history, and occupational exposure to asbestos, researchers at two major cancer centers have determined. The findings, published in the Journal of the National Cancer Institute (2003;95:470–478), have been encapsulated in a simple interactive software program that can be used online or downloaded for later use. “It's quite self-explanatory,” said first author Peter B. Bach, MD, of the department of epidemiology and biostatistics at Memorial Sloan-Kettering Cancer Center. We're getting the general public logging on.” The prediction tool can be used by people between the ages of 50 and 75, who have smoked 10 to 60 cigarettes a day for 25 to 55 years, and who either currently smoke or quit less than 20 years ago. Dr. Bach, with colleagues from his institution and Fred Hutchinson Cancer Research Center, tackled the prediction issue in part to help doctors and their patients balance the risks and benefits of screening for lung cancer. The high lung cancer mortality—expected to reach 157,200 this year, according to the American Cancer Society—is driving an increasing demand among smokers for helical computed tomography (CT) screening for the disease. But, Dr. Bach said in an interview, such screening delivers a high proportion of false positives, with consequent cost and anxiety. “CT scanning for lung cancer looks promising, but it also detects abnormalities in the lung, which cause anxiety and lead to cost, that are actually harmless,” Dr. Bach said. “That's the problem and the strength of CT-scanning—it's highly sensitive.” Knowing the risk of lung cancer would help patients decide whether to undergo CT-scanning, he said. Also Useful for Clinical Trials A simple risk-assessment tool would also be useful for those designing clinical trials, he said. “Alternative selection criteria might lead to increased numbers of cancers per person enrolled,” with a consequent increase in statistical power and decrease in cost and logistical efforts, Dr. Bach said. The questions with any kind of risk prediction are two-fold, he noted: Can it be made useful for individuals, and does the risk vary broadly enough to make distinctions worthwhile? “If you can predict generically, but you have a very low confidence of being on target for an individual, it's not very helpful.” On the other hand, the prediction may be accurate for individuals, but the differences could turn out to be small. “If the high risk is 8% and the low risk is 6%, then being able to distinguish doesn't get anyone very far,” Dr. Bach said. Risk Varies by Factor of 20 or More What he and his colleagues have found is that it is possible to predict individual risk—in a subset of people with several risk factors—and that the variation in risk varies by a factor of 20 or more.Figure: Peter B. Bach, MD: “To the extent that our model can differentiate individuals of different risks, it may serve as a useful adjunct to both investigators and patients, perhaps playing a role similar to risk prediction models for colon cancer and breast cancer.”The researchers developed their model by reviewing data from a large lung cancer prevention trial—the Carotene and Retinol Efficacy Trial (CARET), conducted by Fred Hutchinson in the late 1980s and early 1990s. The study—multicenter, randomized, and controlled—enrolled 14,254 heavy smokers between the ages of 50 and 69, and 4,060 asbestos-exposed men, aged 45 to 69, who were either current or former smokers. The CARET study was stopped in January 1996, but “all of the people were followed for years and years and years,” providing a treasure trove of data on who developed cancer and who did not, Dr. Bach noted. The predictors—age, sex, prior exposure to asbestos, duration of smoking, average amount smoked per day, and duration of abstinence in the case of former smokers—were chosen for two reasons: all are easily determined from the clinical history and all are established or strongly suspected risk factors for lung cancer. The researchers analyzed the CARET data for five of the study's sites and then used their findings to predict what would be seen on a sixth site; the predictions closely matched reality, Dr. Bach said, implying that the model is generalizable to other populations of smokers. The factors that appear to play the main role are age, length of smoking, amount smoked, and occupational exposure to asbestos. Sex did not appear to be related to risk, and length of time off tobacco also showed no effect. “We didn't see much in the way of evidence that there is a healing effect” of quitting, Dr. Bach said. The variation in risk was found by using the model on 300 people who volunteered for a continuing study of CT-scanning at the Mayo Clinic, Dr. Bach said. The 10-year risk ranged from 0.8% for a 51-year-old women who smoked one pack a day for 28 years but had quit smoking nine years previously, to 15% for a 68-year-old man who has smoked two packs a day for 50 years. (His risk drops to 11% if he stops smoking immediately.) The first case, Dr. Bach said, points out the difficulty involved in CT-scanning: The woman's risk of lung cancer in the next decade is less than one in 100, yet there's a 20%-to-50% chance a CT scan will find something in her lung. The researchers also looked at the subset of 201 patients who meet the eligibility criteria for the National Lung Screening Trial, a randomized, controlled trial of lung cancer screening that is now enrolling patients. “The question there is a little bit different,” Dr. Bach said. “If you're going to do a prevention trial, will it help to use risk prediction to target those who should be enrolled?” In fact, according to the model, the lowest risk quartile of the 201 Mayo Clinic patients would account for only 8% of the cancers, while the highest quartile would account for more than half, he said. Long-time lung cancer expert Paul A. Bunn Jr., MD, 2002–2003 President of the American Cancer Society and Director of the University of Colorado Cancer Center, said the research is important, because it defines how important age, sex, and smoking history are in finding risk groups. “One of the main reasons it's important is that as we enter the area of chemoprevention and screening, it's vital that we study the appropriate groups,” he said. “For example, maybe it is not appropriate to do studies in all smokers, because the risk is not that high.” Even former smokers—who account for half of all new lung cancers every year in the US—might be usefully broken down into different risk groups, he said. “If you're doing chemoprevention studies, you'd certainly want to include these people,” but the study by Dr. Bach and his colleagues shows that the worst risk for former smokers was about 10%. The question is what else might be used to find a higher-risk subgroup for a study, Dr. Bunn explained. For instance, he said, researchers at his institution are using sputum cytology as a test, in a cohort of 2,500 people who have smoked a minimum of 30 pack-years (a pack of cigarettes a day for 30 years). In those people, Dr. Bunn said, a moderate atypia or worse means a five-year risk of lung cancer of 18%—sharply higher than even the highest risk found in the study by Dr. Bach's group. His coauthors were Michael W. Kattan, PhD; Mark D. Thornquist, PhD; Mark G. Kris, MD; Ramsey C. Tate; Matt J. Barnett, MS; Lillian J. Hsieh; and Colin B. Begg, PhD. Prediction Tool Online The prediction tool can be accessed at www.mskcc.org/PredictionTools/LungCancer