Lung Cancer Risk Prediction Models
Absolute Risk Prediction Models
Absolute cancer risk is the probability that an individual with given risk factors and a given age will develop cancer over a defined period of time. Examples of these risk factors include race, age, sex, genetics, body mass index, family history of cancer, history of tobacco use, use of aspirin and nonsteroidal anti-inflammatory drugs (NSAIDS), physical activity, use of hormone replacement therapy, reproductive factors, history of cancer screening, and dietary factors.
Developing statistical models that estimate the probability of developing cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk. These types of models also will be useful for designing future chemoprevention and screening intervention trials in individuals at high risk of specific cancers in the general population.
The following risk prediction models are intended primarily for research use and have been peer-reviewed, meaning the methodology and results of these models have been evaluated by qualified scientists and clinicians and published in scientific and medical journals.
- Voss JS, Iqbal S, Jenkins SM, et al. Development of a multivariate model to predict the likelihood of carcinoma in patients with indeterminate peripheral lung nodules after a nondiagnostic bronchoscopic evaluation. Hum Path. Jan 2014;45(1):41-47.
- Iyen-Omofoman B, Tata LJ, Baldwin DR, Smith CJ, Hubbard RB. Using socio-demographic and early clinical features in general practice to identify people with lung cancer earlier. Thorax. May 2013;68(5):451-459.
- Spitz MR, Amos CI, Land S, et al. Role of selected genetic variants in lung cancer risk in African Americans. J Thorac Oncol. Apr 2013;8(4):391-397.
- Ahmed K, Emran AA, Jesmin T, Mukti RF, Rahman MZ, Ahmed F. Early detection of lung cancer risk using data mining. Asian Pac J Cancer Prev. 2013;14(1):595-598.
- Park S, Nam BH, Yang HR, et al. Individualized risk prediction model for lung cancer in Korean men. PloS One. 2013;8(2):e54823.
- Li H, Yang L, Zhao X, et al. Prediction of lung cancer risk in a Chinese population using a multifactorial genetic model. BMC Med Genet. 2012;13:118.
- Lin H, Zhong WZ, Yang XN, et al. A clinical model to estimate the pretest probability of lung cancer, based on 1198 pedigrees in China. J Thorac Oncol. Oct 2012;7(10):1534-1540.
- Raji OY, Duffy SW, Agbaje OF, et al. Predictive accuracy of the Liverpool Lung Project risk model for stratifying patients for computed tomography screening for lung cancer: a case-control and cohort validation study. Ann Intern Med. Aug 21 2012;157(4):242-250.
- Hoggart C, Brennan P, Tjonneland A, et al. A Risk Model for Lung Cancer Incidence. Cancer Prev Res (Phila). Apr 11 2012;5(6):834-836.
- Maisonneuve P, Bagnardi V, Bellomi M, et al. Lung Cancer Risk Prediction to Select Smokers for Screening CT--a Model Based on the Italian COSMOS Trial. Cancer Prev Res (Phila). Nov 2011;4(11):1778-1789.
- Tammemagi CM, Pinsky PF, Caporaso NE, et al. Lung cancer risk prediction: Prostate, Lung, Colorectal And Ovarian Cancer Screening Trial models and validation. J Natl Cancer Inst. Jul 6 2011;103(13):1058-1068.
- Raji OY, Agbaje OF, Duffy SW, Cassidy A, Field JK. Incorporation of a genetic factor into an epidemiologic model for prediction of individual risk of lung cancer: the Liverpool Lung Project. Cancer Prev Res (Phila). May 2010;3(5):664-669.
- Foy M, Spitz MR, Kimmel M, Gorlova OY. A smoking-based carcinogenesis model for lung cancer risk prediction. Int J Cancer. Dec 7 2010.
- Young RP, Hopkins RJ, Hay BA, et al. Lung cancer susceptibility model based on age, family history and genetic variants. PloS one. 2009;4(4):e5302.
- Deng L, Kimmel M, Foy M, Spitz M, Wei Q, Gorlova O. Estimation of the effects of smoking and DNA repair capacity on coefficients of a carcinogenesis model for lung cancer. Int J Cancer. 2008 Nov 11.
- Spitz MR, Etzel CJ, Dong Q, Amos CI, Wei Q, Wu X, Hong WK. An expanded risk prediction model for lung cancer. Cancer Prev Res (Phila Pa). 2008 Sep;1(4):250-4.
- Cassidy A, Myles JP, van Tongeren M, Page RD, Liloglou T, Duffy SW, Field JK. The LLP risk model: an individual risk prediction model for lung cancer. Br J Cancer. 2008 Jan 29;98(2):270-6.
- Etzel CJ, Kachroo S, Liu M, D'Amelio A, Dong Q, Cote ML, Wenzlaff AS, Hong WK, Greisinger AJ, Schwartz AG, Sptiz MR. Development and Validation of a Lung Cancer Risk Prediction Model for African Americans. Cancer Prev Res. 2008;1(4):255-65.
- Spitz MR, Hong WK, Amos CI, Wu X, Schabath MB, Dong Q, Shete S, Etzel CJ. A risk model for prediction of lung cancer. J Natl Cancer Inst. 2007 May 2;99(9):715-26.
- Cassidy A, Myles JP, Liloglou T, Duffy SW, Field JK. Defining high-risk individuals in a population-based molecular-epidemiological study of lung cancer. Int J Oncol. 2006 May;28(5):1295-301.
- Bach PB, Kattan MW, Thornquist MD, Kris MG, Tate RC, Barnett MJ, Hsieh LJ, Begg CB. Variations in lung cancer risk among smokers. J Natl Cancer Inst. 2003 Mar 19;95(6):470-8.
- Peto R, Darby S, Deo H, Silcocks P, Whitley E, Doll R. Smoking, smoking cessation, and lung cancer in the UK since 1950: combination of national statistics with two case-control studies. BMJ. 2000 Aug 5;321(7257):323-9.
- Prindiville SA, Byers T, Hirsch FR, Franklin WA, Miller YE, Vu KO, Wolf HJ, Baron AE, Shroyer KR, Zeng C, Kennedy TC, Bunn PA. Sputum cytological atypia as a predictor of incident lung cancer in a cohort of heavy smokers with airflow obstruction. Cancer Epidemiol Biomarkers Prev. 2003 Oct;12(10):987-93.