U.S National Institutes fo Health | cancer.gov NCI Logo

Cancer Intervention and Surveillance Modeling Network

Modeling to guide public health research and priorities


On this page:

Breast Working Group


Kurian AW, Munoz DF, Rust P, Schackmann EA, Smith M, Clarke L, Mills MA, Plevritis SK. Online Tool to Guide Decisions for BRCA1/2 Mutation Carriers. J Clin Oncol 2012 Feb 10;30(5):497-506. [Abstract]

Lin RS, Plevritis SK. Comparing the benefits of screening for breast cancer and lung cancer using a novel natural history model. Cancer Causes Control 2012 Jan;23(1):175-85. [Abstract]


Edwards-Bennett SM. Racial disparities in breast cancer mortality--letter. Cancer Epidemiol Biomarkers Prev 2011 May;20(5):1046; author reply 1047. [Abstract]

Mandelblatt JS, Cronin KA, Berry DA, Chang Y, de Koning HJ, Lee SJ, Plevritis SK, Schechter CB, Stout NK, van Ravesteyn NT, Zelen M, Feuer EJ. Modeling the impact of population screening on breast cancer mortality in the United States. Breast 2011 Oct;20 Suppl 3:S75-81. [Abstract]

Mandelblatt JS, Stout N, Trentham-Dietz A. To screen or not to screen women in their 40s for breast cancer: is personalized risk-based screening the answer? Ann Intern Med 2011 Jul 5;155(1):58-60. [Abstract]

Trentham-Dietz A, Sprague BL, Alagoz O, Reaidi P, Rosenberg M, Gangnon RE, Stout NK. The Impact of Detection and Treatment of Carcinoma In Situ on Breast Cancer Mortality Cancer. Epidemiol Biomarkers Prev April 2011 20:720. [Abstract]

van Ravesteyn NT, Heijnsdijk EA, de Koning HJ. More on screening mammography. N Engl J Med 2011 Jan 20;364(3):282-3; author reply 285-6. [Abstract]

van Ravesteyn NT, Heijnsdijk EA, Draisma G, de Koning HJ. Prediction of higher mortality reduction for the UK Breast Screening Frequency Trial: a model-based approach on screening intervals. Br J Cancer 2011 Sep 27;105(7):1082-8. doi: 10.1038/bjc.2011.300. [Abstract]

van Ravesteyn NT, Schechter CB, Near AM, Heijnsdijk EA, Stoto MA, Draisma G, de Koning HJ, Mandelblatt JS. Race-specific impact of natural history, mammography screening, and adjuvant treatment on breast cancer mortality rates in the United States. Cancer Epidemiol Biomarkers Prev 2011 Jan;20(1):112-22. [Abstract]


Bailey SL, Sigal BM, Plevritis SK. A simulation model investigating the impact of tumor volume doubling time and mammographic tumor detectability on screening outcomes in women aged 40-49 years. J Natl Cancer Inst 2010 Aug 18;102(16):1263-71. [Abstract]

Kalager M, Zelen M, Langmark F, Adami HO. Effect of screening mammography on breast-cancer mortality in Norway. N Engl J Med 2010 Sep 23;363(13):1203-10. [Abstract]

Kurian AW, Sigal BM, Plevritis SK. Survival analysis of cancer risk reduction strategies for BRCA1/2 mutation carriers. J Clin Oncol 2010 Jan 10;28(2):222-31. [Abstract]


Mandelblatt JS, Cronin KA, Bailey S, Berry DA, de Koning H J, Draisma G, Huang H, Lee SJ, Munsell M, Plevritis SK, Ravdin P, Schechter CB, Sigal B, Stoto MA, Stout NK, van Ravesteyn NT, Venier J, Zelen M, Feuer EJ. Effects of mammography screening under different screening schedules: model estimates of potential benefits and harms. Ann Intern Med 2009;151:738-47. [Abstract]


Lee SJ, Zelen M. Mortality modeling of early detection programs. Biometrics 2008;64:386-95. [Abstract]

Mandelblatt JS, Potosky AL. On the road to improving the quality of breast cancer care: a distance still to travel. Med Care 2008 Aug;46(8):759-61. [Abstract]

Mandelblatt JS, Silliman R. Hanging in the balance: making decisions about the benefits and harms of breast cancer screening among the oldest old without a safety net of scientific evidence. J Clin Oncol 2008 Dec 15.

Stout NK, Goldie SJ. Keeping down the noise: common random numbers for disease simulation modeling. Health Care Manag Sci 2008 Dec;11(4):399-406. [Abstract]

Tosteson ANA, Stout NK, Fryback DG, Acharyya S, Herman B, Hannah H, Pisano E. Cost-effectiveness of digital mammography breast cancer screening: results from ACRIN DMIST. Ann Intern Med 2008;148(1):1-10. [Abstract]


Hanin LG, Yakovlev A. Identifiability of the joint distribution of age and tumor size at detection in the presence of screening. Math Biosci 2007 Aug;208(2):644-57. [Abstract]

Plevritis SK, Salzman P, Sigal BM, Glynn PW. A natural history model of stage progression applied to breast cancer. Stat Med 2007 Feb 10;26(3):581-95. [Abstract]

Ravdin PM, Cronin KA, Howlader N, Berg CD, Chlebowski RT, Feuer EJ, Edwards BK, Berry DA. The decrease in breast-cancer incidence in 2003 in the United States. N Engl J Med 2007;356:1670-74. [Abstract]


Cancer Intervention and Surveillance Modeling Network (CISNET) Breast Cancer Collaborators. The impact of mammography and adjuvant therapy on U.S. breast cancer mortality (1975-2000): Collective Results from the Cancer Intervention and Surveillance Modeling Network. J Natl Cancer Inst Monographs 2006;36:1-126.

Cancer Intervention and Surveillance Modeling Network (CISNET) Breast Cancer Collaborators. Executive summary. J Natl Cancer Inst Monographs 2006;(36):1-2. [Extract]

Feuer EJ. Chapter 1: Modeling the impact of adjuvant therapy and screening mammography on U.S. breast cancer mortality between 1975 and 2000: introduction to the problem. J Natl Cancer Inst Monographs 2006;(36):2-6. [Extract]

Mariotto AB, Feuer EJ, Harlan LC, Abrams J. Chapter 2: Dissemination of adjuvant multiagent chemotherapy and tamoxifen for breast cancer in the United States using estrogen receptor information: 1975-1999. J Natl Cancer Inst Monographs 2006;(36):7-15. [Abstract]

Rosenberg MA. Chapter 3: Competing risks to breast cancer mortality. J Natl Cancer Inst Monographs 2006;(36):15-9. [Abstract]

Holford TR, Cronin KA, Mariotto AB, Feuer EJ. Chapter 4: Changing patterns in breast cancer incidence trends. J Natl Cancer Inst Monographs 2006;(36):19-25. [Abstract]

Cronin KA, Mariotto AB, Clarke LD, Feuer EJ. Chapter 5: Additional common inputs for analyzing impact of adjuvant therapy and mammography on U.S. mortality. J Natl Cancer Inst Monographs 2006;(36):26-9. [Abstract]

Berry DA, Inoue L, Shen Y, Venier J, Cohen D, Bondy M, Theriault R, Munsell MF. Chapter 6: Modeling the impact of treatment and screening on U.S. breast cancer mortality: a bayesian approach J Natl Cancer Inst Monographs 2006;(36):30-6. [Abstract]

Fryback DG, Stout NK, Rosenberg MA, Trentham-Dietz A, Kuruchittham V, Remington PL. Chapter 7: The Wisconsin Breast Cancer Epidemiology Simulation Model. J Natl Cancer Inst Monographs 2006;(36):37-47. [Abstract]

Mandelblatt J, Schechter CB, Lawrence W, Yi B, Cullen J. Chapter 8: The SPECTRUM population model of the impact of screening and treatment on U.S. breast cancer trends from 1975 to 2000: principles and practice of the model methods. J Natl Cancer Inst Monographs 2006;(36):47-55. [Abstract]

Tan SYGL, van Oortmarssen GJ, de Koning HJ, Boer R, Habbema JD. Chapter 9: The MISCAN-Fadia Continuous Tumor Growth Model for Breast Cancer. J Natl Cancer Inst Monographs 2006;(36):56-65. [Abstract]

Hanin LG, Miller A, Zorin AV, Yakovlev AY. Chapter 10: The University of Rochester Model of Breast Cancer Detection and Survival. J Natl Cancer Inst Monographs 2006;(36):66-78. [Abstract]

Lee S, Zelen M. Chapter 11: A stochastic model for predicting the mortality of breast cancer. J Natl Cancer Inst Monographs 2006;(36):79-86. [Abstract]

Plevritis SK, Sigal BM, Salzman P, Rosenberg J, Glynn P.Chapter 12: A stochastic simulation model of U.S. breast cancer mortality trends from 1975 to 2000. J Natl Cancer Inst Monographs 2006;(36):86-95. [Abstract]

Clarke LD, Plevritis SK, Boer R, Cronin KA, Feuer EJ. Chapter 13: A comparative review of CISNET breast models used to analyze U.S. breast cancer incidence and mortality trends. J Natl Cancer Inst Monographs 2006;(36):96-105. [Abstract]

Habbema JD, Tan SYGL, Cronin KA. Chapter 14: Impact of mammography on U.S. breast cancer mortality, 1975–2000: are intermediate outcome measures informative?J Natl Cancer Inst Monographs 2006;(36):105-11. [Abstract]

Cronin KA, Feuer EJ, Clarke LD, Plevritis SK.Chapter 15: Impact of adjuvant therapy and mammography on U.S. mortality from 1975 to 2000: comparison of mortality results from the CISNET breast cancer base case analysis. J Natl Cancer Inst Monographs 2006;(36):112-21. [Abstract]

Habbema JD, Schechter CB, Cronin KA, Clarke LD, Feuer EJ. Chapter 16: Modeling cancer natural history, epidemiology, and control: reflections on the CISNET breast group experience. J Natl Cancer Inst Monographs 2006;(36):122-26. [Abstract]

Hanin LG, Pavlova LV. Optimal regimens of cancer screening. In: Edler L, Kitsos CP, editors. Recent advances in quantitative methods in cancer and human health risk assessment. New York: Wiley; 2006. Jun p. 177-91. [Summary]

Liang W, Kasman D, Wang JH, Yuan EH, Mandelblatt JS. Communication between older women and physicians: preliminary implications for satisfaction and intention to have mammography. Patient Educ Couns 2006 Dec;64(1-3):387-92. [Abstract]

Plevritis SK, Kurian AW, Sigal BM, Daniel BL, Ikeda DM, Stockdale FE, Garber AM. Cost-effectiveness of screening BRCA1/2 mutation carriers with breast magnetic resonance imaging. JAMA 2006 May 24;295(20):2374-84. [Abstract]

Stout NK, Rosenberg MA, Trentham-Dietz A, Smith MA, Robinson SM, Fryback DG. Retrospective cost-effectiveness analysis of screening mammography. J Natl Cancer Inst 2006;98(11):774-782. [Abstract]


Berry DA, Cronin KA, Plevritis SK, Fryback DG, Clarke L, Zelen M, Mandelblatt JS, Yakovlev AY, Habberna JDF, Feuer EJ. Effect of screening and adjuvant therapy on mortality from breast cancer. New Eng J Med 2005 Oct 27;353(17):12-20. [Abstract]

Cronin KA,Yu B, Krapcho M, Miglioretti DL, Fay MP, Izmirlian G, Ballard-Barbash R, Geller BM, Feuer EJ. Modeling the dissemination of mammography in the United States. Cancer Causes Control 2005;16:701-712. [Abstract]

Mandelblatt JS, Schechter CB, Yabroff KR, Lawrence W, Dignam J, Extermann M, Fox S, Orosz G, Silliman R, Cullen J, Balducci L. Breast Cancer In Older Women Research Consortium. Toward optimal screening strategies for older women. J Gen Intern Med 2005 Jun;20(6):487-96. [Abstract]

Pignone M, Saha S, Hoerger T, Lohr KN, Teutsch S, Mandelblatt J. Challenges in systematic reviews of economic analyses. Ann Intern Med 2005 Jun 21;142(12 Pt 2):1073-9. [Abstract]

Rosenberg J, Chia YL, Plevritis S. The effect of age, race, tumor size, tumor grade, and disease stage on invasive ductal breast cancer survival in the U.S. SEER database. Breast Cancer Res Treat 2005 Jan;89(1):47-54. [Abstract]

Shen Y, Yang Y, Inoue LY, Munsell MF, Miller AB, Berry DA. Role of detection method in predicting breast cancer survival: analysis of randomized screening trials. J Natl Cancer Inst 2005 Aug 17;97(16):1195-203. [Abstract]

Shen Y, Zelen M. Robust modeling in screening studies: estimation of sensitivity and preclinical sojourn time distribution. Biostat 2005;6(4):604-14. [Abstract]

Zelen M. Risks of cancer and families. J Natl Cancer Inst 2005 Nov 2;97(21):1556-7. [Abstract]

Zorin AV, Edler L, Hanin LG, Yakovlev AY. Estimating the natural history of breast cancer from bivariate data on age and tumor size at diagnosis. In: Edle L, Kitsos CP, editors. Recent Advances in Quantitative Methods for Cancer and Human Health Risk Assessment. New York: Wiley; 2005. p. 317-27. [Summary]


Andersen LD, Remington PL, Trentham-Dietz A, Robert S. Community trends in the early detection of breast cancer in Wisconsin, 1980-1998. Am J Prev Med 2004 JAn;26(1):51-5. [Abstract]

Boer R, Plevritis S, Clarke L. Diversity of model approaches for breast cancer screening: a review of model assumptions by the Cancer Intervention and Surveillance Network (CISNET) Breast Cancer Groups. Stat Methods Med Res 2004 Dec;13(6):525-38. [Abstract]

Boucher KM, Asselain B, Tsodikov AD, Yakovlev AY. Semiparametric versus parametric regression analysis based on the bounded cumulative hazard model: An application to breast cancer recurrence. In: Nikulin MS, Balakrishnan N, Mesban M, Limnios N, editors. Parametric and Semiparametric Models with Applications to Reliability, Survival Analysis, and Quality of Life. Boston, MA: Birhauser; 2004. p. 399-418.

Chia L, Salzman P, Plevritis SK, Glynn PW. Simulation-based parameter estimation for complex models: a breast cancer natural history modeling illustration. Stat Methods Med Res 2004 Dec;13(6):507-24. [Abstract]

Davidov O, Zelen M. Overdiagnosis in early detection programs. Biostat 2004;5(4):603-13. [Abstract]

Hanin LG, Yakovlev AY. Multivariate distributions of clinical covariates at the time of cancer detection. Stat Methods Med Res 2004 Dec;13(6):457-89. [Abstract]

Hu P, Zelen M. Planning of randomized early detection trials. Stat Methods Med Res 2004;13:491-506. [Abstract]

Lee S, Huang H, Zelen M. Early detection of disease and the scheduling of examinations. Stat Methods Med Res 2004;13:443-56. [Abstract]

Mandelblatt J, Schechter CB, Yabroff KR, Lawrence W, Dignam J, Muennig P. Benefits and costs of interventions to improve breast cancer outcomes in African American women. J Clin Oncol 2004 Jul 1;22(13):2554-66. [Abstract]

Zelen M. Forward and backward recurrence times and length biased sampling: Age specific models. Lifetime Data Anal 2004;10:325-34. [Abstract]


Davidov O, Zelen M. The theory of case-control studies for early detection programs. Biostat 2003;4:411-21. [Abstract]

Lee SJ, Zelen M. Modeling the early detection of breast cancer. Ann Oncol 2003;14:1199-202. [Abstract]

Mandelblatt J, Saha S, Teutsch S. The cost-effectiveness of screening mammography beyond age 65 years: a systematic review for the U.S. Preventive Services Task Force. Ann Intern Med 2003 Nov 18;139(10):835-42. [Abstract]

Polsky D, Mandelblatt JS, Weeks JC, Venditti L, Hwang YT, Glick HA, Hadley J, Schulman KA. Economic evaluation of breast cancer treatment: considering the value of patient choice. J Clin Oncol 15 Mar 2003;21(6):1139-46. [Abstract]

Stout NK, Rosenberg MA, Fryback DG. Does diagnosis by screening mammography lead to a gain in life expectancy for women with breast cancer and if so how much? Med Decis Making 2003;23(6):552.

Stout NK, Rosenberg MA, Remington PL, Trentham-Dietz A, Fryback DG. Can routine screening really reduce breast cancer mortality by 40-60%. Med Decis Making 2003;23(6):559.

Tan SYGL, van Oortmarssen GJ, Piersma N. Estimating parameters of a microsimulation model for breast cancer screening using the score function method. Ann Oper Res 2003;119:43-61. [Abstract]

Yabroff KR, Washington KS, Leader A, Neilson E, Mandelblatt J. Is the promise of cancer-screening programs being compromised? Quality of follow-up care after abnormal screening results. Med Care Res Rev 2003 Sep;60(3):294-331. [Abstract]


Hanin L. Identification problem for stochastic models with application to carcinogenesis, cancer detection and radiation biology. Discrete Dyn Nat Soc 2002;7:177-89. [Absract]

Hu P, Zelen M. Experimental design issues for the early detection of disease: novel designs. Biostat 2002;3(3):299-313. [Abstract]

Lee SJ, Zelen M. Statistical models for screening: planning public health programs. Cancer Treat Res 2002;113:19-36. [Abstract]

Mariotto A, Feuer EJ, Harlan LC, Wun LM, Johnson KA, Abrams J. Trends in use of adjuvant multi-agent chemotherapy and tamoxifen for breast cancer in the United States: 1975-1999. J Natl Cancer Inst 2002 Nov 6;94(21):1626-34. [Abstract]

Parmigiani G, Skates S, Zelen M. Modeling and optimization in early detection programs with a single exam. Biometrics 2002;58:30-6. [Abstract]

Zelen M, Lee SJ. Models and the early detection of disease: methodological considerations. Cancer Treat Res 2002;113:1-18. [Abstract]


Bartoszynski R, Edler L, Hanin L, Kopp-Schneider A, Pavlova L, Tsodikov A, Zorin A, Yakovlev AY. Modeling cancer detection: tumor size as a source of information on unobservable stages of carcinogenesis. Math Biosci 2001 Jun;171(2):113-42. [Abstract]

Hanin, LG; Tsodikov, AD; Yakovlev, AY. Optimal schedules of cancer surveillance and tumor size at detection. Math Comp Modell. 2001;33(12):1419-30. [Abstract]

Saha S, Hoerger TJ, Pignone MP, Teutsch SM, Helfand M, Mandelblatt JS; Cost Work Group, Third U.S. Preventive Services Task Force. The art and science of incorporating cost-effectiveness into evidence-based recommendations for clinical preventive services. Am J Prev Med 2001 Apr;20(3 Suppl):36-43. [Abstract]

Shen Y, Wu D, Zelen M. Testing the independence of two diagnostic tests. Biometrics 2001 Dec;57(4):1009-17. [Abstract]

Shen Y, Zelen M. Screening sensitivity and sojourn time from breast cancer early detection clinical trials: mammograms and physical examinations. J Clin Oncol 2001 Aug 1;19(15):3490-9. [Abstract]

Yabroff KR, O'Malley A, Mangan P, Mandelblatt J. Inreach and outreach interventions to improve mammography use. J Am Med Womens Assoc 2001;56(4):166-73, 188. [Abstract]

Return to top

Colorectal Working Group


Rutter CM, Johnson E, Miglioretti DL, Mandelson MT, Inadomi J, Buist DS. Adverse events after screening and follow-up colonoscopy. Cancer Causes Control 2012 Feb;23(2):289-96. [Abstract]

Zauber AG, Winawer SJ, O'Brien MJ, Lansdorp-Vogelaar I, van Ballegooijen M, Hankey BF, Shi W, Bond JH, Schapiro M, Panish JF, Stewart ET, Waye JD. Colonoscopic polypectomy and long-term prevention of colorectal-cancer deaths. N Engl J Med 2012 Feb 23;366(8):687-96. [Abstract]


Bradley CJ, Lansdorp-Vogelaar I, Yabroff KR, Dahman B, Mariotto A, Feuer EJ, Brown ML. Productivity savings from colorectal cancer prevention and control strategies. Am J Prev Med 2011 Aug;41(2):e5-e14. [Abstract]

Berrington de González A, Kim KP, Knudsen AB, Lansdorp-Vogelaar I, Rutter CM, Smith-Bindman R, Yee J, Kuntz KM, van Ballegooijen M, Zauber AG, Berg CD. Radiation-related cancer risks from CT colonography screening: a risk-benefit analysis. AJR Am J Roentgenol 2011 Apr;196(4):816-23. [Abstract]

Haug U, Knudsen AB, Brenner H, Kuntz KM. Is fecal occult blood testing more sensitive for left- versus right-sided colorectal neoplasia? A systematic literature review. Expert Rev Mol Diagn 2011 Jul;11(6):605-16. Review. [Abstract]

Haug U, Kuntz KM, Knudsen AB, Hundt S, Brenner H. Sensitivity of immunochemical faecal occult blood testing for detecting left- vs right-sided colorectal neoplasia. Br J Cancer 2011 May 24;104(11):1779-85. [Abstract]

Kuntz KM, Lansdorp-Vogelaar I, Rutter CM, Knudsen AB, van Ballegooijen M, Savarino JE, Feuer EJ, Zauber AG. A systematic comparison of microsimulation models of colorectal cancer: the role of assumptions about adenoma progression. Med Decis Making 2011 Jul-Aug;31(4):530-9. [Abstract]

Lansdorp-Vogelaar I, Knudsen AB, Brenner H. Cost-effectiveness of colorectal cancer screening. Epidemiol Rev 2011 Jul;33(1):88-100. Review. [Abstract]

Rutter CM, Knudsen AB, Pandharipande PV. Computer disease simulation models: integrating evidence for health policy. Acad Radiol 2011 Sep;18(9):1077-86. Review. [Abstract]

Rutter CM, Miglioretti DL, Savarino JE. Evaluating risk factor assumptions: a simulation-based approach. BMC Med Inform Decis Mak 2011 Sep 7;11:55. [Abstract]

Rutter CM, Zaslavsky AM, Feuer EJ. Dynamic microsimulation models for health outcomes: a review. Med Decis Making 2011 Jan-Feb;31(1):10-8. Review. [Abstract]

van Ballegooijen M, Rutter CM, Knudsen AB, Zauber AG, Savarino JE, Lansdorp-Vogelaar I, Boer R, Feuer EJ, Habbema JD, Kuntz KM. Clarifying differences in natural history between models of screening: the case of colorectal cancer. Med Decis Making 2011 Jul-Aug;31(4):540-9. [Abstract]

Vanness DJ, Knudsen AB, Lansdorp-Vogelaar I, Rutter CM, Gareen IF, Herman BA, Kuntz KM, Zauber AG, van Ballegooijen M, Feuer EJ, Chen MH, Johnson CD. Comparative economic evaluation of data from the ACRIN National CT Colonography Trial with three cancer intervention and surveillance modeling network microsimulations. Radiology 2011 Nov;261(2):487-98. [Abstract]


Edwards BK, Ward E, Kohler BA, Eheman C, Zauber AG, Anderson RN, Jemal A, Schymura MJ, Lansdorp-Vogelaar I, Seeff LC, van Ballegooijen M, Goede SL, Ries LA. Annual report to the nation on the status of cancer, 1975-2006, featuring colorectal cancer trends and impact of interventions (risk factors, screening, and treatment) to reduce future rates. Cancer 2010 Feb 1;116(3):544-73. [Abstract]

Knudsen AB, Lansdorp-Vogelaar I, Rutter CM, Savarino JE, van Ballegooijen M, Kuntz KM, Zauber AG. Cost-effectiveness of computed tomographic colonography screening for colorectal cancer in the medicare population. J Natl Cancer Inst. 2010 Aug 18;102(16):1238-1252. [Abstract]

Lansdorp-Vogelaar I, Knudsen AB, Brenner H. Cost-effectiveness of colorectal cancer screening - an overview. Best Pract Res Clin Gastroenterol 2010 Aug;24(4):439-49. [Abstract]

Lansdorp-Vogelaar I, Kuntz KM, Knudsen AB, Wilschut JA, Zauber AG, van Ballegooijen M. Stool DNA testing to screen for colorectal cancer in the Medicare population: a cost-effectiveness analysis. Ann Intern Med 2010 Sep 21;153(6):368-77. [Abstract]

Rutter CM, Savarino JE. An evidence-based microsimulation model for colorectal cancer: validation and application. Cancer Epidemiol Biomarkers Prev. 2010;19(8):1992-2002. [Abstract]

Rutter CM, Zaslavsky A, Feuer E. Dynamic microsimulation models for health outcomes: a review. Med Decis Making 2010 May 18. [Epub ahead of print] [Abstract]

van Ballegooijen M, Boer R, Zauber AG. Simulation of colorectal cancer screening: what we do and do not know and does it matter. Best Pract Res Clin Gastroenterol 2010 Aug;24(4):427-37. [Abstract]

Zauber AG. Cost-effectiveness of colonoscopy. Gastrointest Endosc Clin N Am 2010 Oct;20(4):751-70. Review. [Abstract]

Zauber AG, van Ballegooijen M, Petitti D, Lansdorp-Vogelaar I. United States Preventive Services Task Force recommendations: age to end screening misunderstood. Dis Colon Rectum 2010 Oct;53(10):1453; author reply 1453. [Abstract]


Bentley TG, Willett WC, Weinstein MC, Kuntz KM. The effects of categorizing continuous variables in decision-analytic models. Med Decis Making 2009 Sep-Oct;29(5):549-56. Epub 2009 Jul 13. [Abstract]

Lansdorp-Vogelaar I, van Ballegooijen M, Zauber AG, Habbema JD, Kuipers EJ. Effect of rising chemotherapy costs on the cost savings of colorectal cancer screening. J Natl Cancer Inst 2009 Sep 24. [Abstract]

Lansdorp-Vogelaar I, van Ballegooijen M, Zauber AG, Boer R, Wilschut J, Winawer SJ, Habbema JD. Individualizing colonoscopy screening by sex and race. Gastrointest Endosc 2009 Jul;70(1):96-108, 108.e1-24. [Abstract]

Lansdorp-Vogelaar I, van Ballegooijen M, Boer R, Zauber A, Habbema JD. A novel hypothesis on the sensitivity of the fecal occult blood test: Results of a joint analysis of 3 randomized controlled trials. Cancer 2009 Jun 1;115(11):2410-9. [Abstract]

Lansdorp-Vogelaar I. Effects of Colorectal Cancer Screening on Population Health - a modeling assessment. PhD thesis for Department of Public Health, Erasmus University, Rotterdam, the Netherlands; April 2009.

Lansdorp-Vogelaar I, van Ballegooijen M, Zauber AG, Boer R, Wilschut J, Habbema JD. At what costs will screening with CT colonography be competitive? A cost-effectiveness approach. Int J Cancer 2009 Mar 1;124(5):1161-8. [Abstract]

Rutter CM, Miglioretti DL, Savarino JE. Bayesian Calibration of Microsimulation Models. J Am Stat Assoc 2009 Dec 1;104(488):1338-1350. [Abstract]

Zauber AG, Knudsen AB, Rutter CM, Lansdorp-Vogelaar I, Savarino JE, van Ballegooijen M, Kuntz KM. Cost-effectiveness of CT Colonography to screen for colorectal cancer. 2009 Jan 22. Available from: http://www.cms.gov/medicare-coverage-database/details/technology-assessments-details.aspx?TAId=58.


Bentley TG, Weinstein MC, Willett WC, Kuntz KM. A cost-effectiveness analysis of folic acid fortification policy in the United States. Public Health Nutr 2008;1:1-13. [Abstract]

Jeon J, Meza R, Moolgavkar SH, Luebeck EG. Evaluation of screening strategies for pre-malignant lesions using a biomathematical approach. Math Biosci 2008;213;56-70. [Abstract]

Miglioretti DL, Brown ER. A marginalized diffusion model for estimating age at first lower endoscopy use from current-status data. J R Stat Soc Ser C Appl Stat 2008;57(1):61-74. [Abstract]

Miglioretti DL, Rutter CM, Bradford SC, Zauber AG, Kessler LG, Feuer EJ, Grossman DC. Improvement in the diagnostic evaluation of a positive fecal occult blood test in an integrated health care organization. Med Care 2008;46(9 Suppl 1):S91-6. [Abstract]

Scherer R, Knudsen A, Pearson SD. Institute for Clinical and Economic Review. Final Appraisal Document. CT Colonography for Colorectal Cancer Screening. 2008 Jan. Available from: http://www.hta.hca.wa.gov/documents/ctc_final_evidence.pdf

Zauber AG, Lansdorp-Vogelaar I, Knudsen AB, Wilschut J, van Ballegooijen M, Kuntz KM. Evaluating test strategies for colorectal cancer screening: a decision analysis for the U.S. Preventive Services Task Force. Ann Intern Med 2008 Nov 4;149(9):659-69. Epub 2008 Oct 6. [Abstract]


Rutter CM, Yu O, Miglioretti DM. A hierarchical non-homogeneous Poisson model for meta-analysis of adenoma counts. Stat Med 2007;26:98-109. [Abstract]

Wang YC, Colditz GA, Kuntz KM. Forecasting the obesity epidemic in the aging U.S. population. Obesity 2007 Nov;15(11):2855-65. [Abstract]

Zauber AG, Lansdorp-Vogelaar I, Wilschut J, Knudsen AB, van Ballegooijen M, Kuntz KM. Cost-effectiveness of DNA stool testing to screen for colorectal cancer: Report to AHRQ and CMS from the Cancer Intervention and Surveillance Modeling Network (CISNET) for MISCAN and SimCRC Models. 2007 Dec 20. Available from: http://www.cms.gov/medicare-coverage-database/details/technology-assessments-details.aspx?TAId=52.


Bentley TG, Willett WC, Weinstein MC, Kuntz KM. Population-level changes in folate intake by age, gender, and race/ethnicity after folic acid fortification. Am J Public Health 2006 Nov;96(11):2040-7. [Abstract]

Vogelaar I, van Ballegooijen M, Schrag D, Boer R, Winawer SJ, Habbema JD, Zauber AG. How much can current interventions reduce colorectal cancer mortality in the U.S.: mortality projections for scenarios of risk-factor modification, screening, and treatment. Cancer 2006 Aug 24;107(7):1624-33. [Abstract]

Winawer SJ, Zauber AG, Fletcher RH, Stillman JS, O'Brien MJ, Levin B, Smith RA, Lieberman DA, Burt RW, Levin TR, Bond JH, Brooks D, Byers T, Hyman N, Kirk L, Thorson A, Simmang C, Johnson D, Rex DK, U.S. Multi-Society Task Force on Colorectal Cancer, American Cancer Society. Guidelines for colonoscopy surveillance after polypectomy: a consensus update by the U.S. Multi-Society Task Force on Colorectal Cancer and the American Cancer Society. Gastroenterology May 2006;130(6):1872-85. [Abstract]

Winawer SJ, Zauber AG, Fletcher RH, Stillman JS, O'Brien MJ, Levin B, Smith RA, Lieberman DA, Burt RW, Levin TR, Bond JH, Brooks D, Byers T, Hyman N, Kirk L, Thorson A, Simmang C, Johnson D, Rex DK. Guidelines for colonoscopy surveillance after polypectomy: a consensus update by the U.S. Multi-Society Task Force on Colorectal Cancer and the American Cancer Society. CA Cancer J Clin 2006;56(3):143-59; quiz 184-5. [Abstract]


de Visser M, van Ballegooijen M, Bloemers SM, van Deventer SJ, Jansen JB, Jespersen J, Kluft C, Meijer GA, Stoker J, de Valk GA, Verweij MF, Vlems FA. Report on the Dutch consensus development meeting for implementation and further development of population screening for colorectal cancer based on FOBT. Cell Oncol 2005;27(1):17-29. [Abstract]

Knudsen AB. Explaining secular trends in colorectal cancer incidence and mortality with an empirically-calibrated microsimulation model [Ph.D. dissertation]. Cambridge, MA: Harvard University. 2005. [Abstract]


Loeve F, Boer R, Zauber AG, van Balleooijen M, van Oortmarssen GJ, Winawer SJ, Habbema JD. National Polyp Study data: evidence for regression of adenomas. Int J Cancer 2004;111:633-9. [Abstract]

Loeve F, van Ballegooijen M, Boer R, Kuipers EJ, Habbema JDF. Colorectal cancer risk in adenoma patients: a nation-wide study. Int J Cancer 2004:111(1):147-41. [Abstract]

Schrag D. The price tag on progress-chemotherapy for colorectal cancer. New Eng J Med 2004;351(4):317-9. [Abstract]


van Ballegooijen M, Habbema JDF, Boer R, Zauber AG, Brown ML. Report to the Agency for Healthcare Research and Quality: a comparison of the cost-effectiveness of fecal occult blood tests with different test characteristics in the context of annual screening in the Medicare population. 2003 Aug. Available from: http://www.cms.gov/medicare-coverage-database/details/technology-assessments-details.aspx?TAId=20.

Return to top

Esophagus Working Group


Hur C, Choi SE, Rubenstein JH, Kong CY, Nishioka NS, Provenzale DT, Inadomi JM. The Cost Effectiveness of Radiofrequency Ablation for Barrett's Esophagus. Gastroenterology 2012 Sep;143(3):567-75. Epub 2012 May 21. [Abstract]


Kong CY, Nattinger KJ, Hayeck TJ, Omer ZB, Wang YC, Spechler SJ, McMahon PM, Gazelle GS, Hur C. The impact of obesity on the rise in esophageal adenocarcinoma incidence: estimates from a disease simulation model. Cancer Epidemiol Biomarkers Prev 2011 Nov;20(11):2450-6. [Abstract]

Return to top

Lung Working Group


Feuer EJ, Moolgavkar SH, Levy DT, Kimmel M, Clarke LD (editors).  The Impact of Tobacco Smoking on U.S. Lung Cancer Mortality (1975-2000):  Collective Results from the Cancer Intervention and Surveillance Modeling Network (CISNET).  Risk Anal  2012; 32 (S1). E-pub Aug 7, 2012. [Journal Web Site]

Bloch M, Backinger CL, Compton WM, Conway K. Standing on the Threshold of Change. Risk Anal  2012; 32 (S1): S6-S13. [Abstract]

Feuer EJ, Levy DT, McCarthy WJ. Chapter 1: The Impact of the Reduction in Tobacco Smoking on U.S. Lung Cancer Mortality, 1975–2000: An Introduction to the Problem. Risk Anal 2012; 32(S1):S6-S13. [Abstract]

Anderson CM, Burns DM, Dodd KW, Feuer EJ. Chapter 2: Birth cohort specific estimates of smoking behaviors for the U.S. population. Risk Anal 2012; 32(S1):S14-S24. [Abstract] [Resources]

Rosenberg MA, Feuer EJ, Yu B, Sun J, Henley SJ, Shanks TG, Anderson CM, McMahon PM, Thun MJ, Burns DM. Chapter 3: Cohort life tables by smoking status, removing lung cancer as a cause of death. Risk Anal 32(S1):S25-S38. [Abstract] [Resources]

Holford TR, Clark L. Chapter 4: Development of the Counterfactual Smoking Histories Used to Assess the Effects of Tobacco Control. Risk Anal 32(S1):S39–S50. [Abstract]

Jeon J, Meza R, Krapcho M, Clarke LD, Byrne J, Levy DT. Chapter 5: Actual and Counterfactual Smoking Prevalence Rates in the U.S. Population via Microsimulation. Risk Anal 2012; 32(S1):S51–S68. [Abstract]

McCarthy WJ, Meza R, Jeon J, Moolgavkar SH. Chapter 6: Lung Cancer in Never Smokers: Epidemiology and Risk Prediction Models. Risk Anal 2012; 32(S1):S69–S84. [Abstract]

Schultz FW, Boern R, de Koning HJ. Chapter 7: Description of MISCAN-Lung, the Erasmus MC Lung Cancer Microsimulation Model for Evaluating Cancer Control Interventions. Risk Anal 2012; 32(S1):S85–S98. [Abstract]

Hazelton WD, Jeon J, Meza R, Moolgavkar SH. Chapter 8: The FHCRC Lung Cancer Model. Risk Anal 2012; 32(S1):S99–S116. [Abstract]

McMahon PM, Kong CY, Johnson BE, Weinstein MC, Weeks JC, Tramontano AC, Cipriano LE, Bouzan C, Gazelle GS. Chapter 9: The MGH-HMS Lung Cancer Policy Model: Tobacco Control Versus Screening. Risk Anal 2012; 32(S1):S117–S124. [Abstract]

Levy DT, Blackman K, Zaloshnja E. Chapter 10: A Macro-Model of Smoking and Lung Cancer: Examining Aggregate Trends in Lung Cancer Rates Using the CPS-I and CPS-II and Two-Stage Clonal Expansion Models. Risk Anal 2012; 32(S1):S125–S141. [Abstract]

Foy M, Deng L, Spitz M, Gorlova O, Kimmel M. Chapter 11: Rice-MD Anderson Lung Cancer Model. Risk Anal 2012; 32(S1):S142–S150. [Abstract]

Holford TR, Ebisu K, McKay L, Oh C, Zheng T. Chapter 12: Yale Lung Cancer Model. Risk Anal 2012; 32(S1):S151–S165. [Abstract]

McMahon PM, Hazelton WD, Kimmel M, Clarke LD. Chapter 13: CISNET Lung Models: Comparison of Model Assumptions and Model Structures. Risk Anal 2012; 32(S1):S166–S178. [Abstract]

Holford TR, Levy DT. Chapter 14: Comparing the Adequacy of Carcinogenesis Models in Estimating U.S. Population Rates for Lung Cancer Mortality. Risk Anal 2012; 32(S1):S179–S189. [Abstract]

Boer R, Moolgavkar SH, Levy DT. Chapter 15: Impact of Tobacco Control on Lung Cancer Mortality in the United States Over the Period 1975–2000—Summary and Limitations. Risk Anal 2012; 32(S1):S190–S201. [Abstract]

Goldwasser DL, Kimmel M. Small median tumor diameter at cure threshold (<20 mm) among aggressive non-small cell lung cancers in male smokers predicts both chest X-ray and CT screening outcomes in a novel simulation framework. Int J Cancer 2012 Apr 17. [Epub ahead of print] [Abstract]

Hazelton WD, Goodman G, Rom WN, Tockman M, Thornquist M, Moolgavkar S, Weissfeld JL, Feng Z. Longitudinal multistage model for lung cancer incidence, mortality, and CT detected indolent and aggressive cancer. Math Biosci 2012 Jun 13. [Abstract]

Moolgavkar SH, Holford TR, Levy DT, Kong CY, Foy M, Clarke L, Jeon J, Hazelton WD, Meza R, Schultz F, McCarthy W, Boer R, Gorlova O, Gazelle GS, Kimmel M, McMahon PM, de Koning HJ, Feuer EJ. Impact of Reduced Tobacco Smoking on Lung Cancer Mortality in the United States During 1975-2000. J Natl Cancer Inst 2012 Mar 14. [Abstract] [Resources]


Shi L, Tian H, McCarthy WJ, Berman B, Wu S, Boer R. Exploring the uncertainties of early detection results: model-based interpretation of mayo lung project. BMC Cancer 2011 Mar 7;11:92. [Abstract]


Abrams DB, Graham AL, Levy DT, Mabry PL, Orleans CT. Boosting population quits through evidence-based cessation treatment and policy. Am J Prev Med 2010 Mar;38(3 Suppl):S351-63. [Abstract]

Foy M, Spitz MR, Kimmel M, Gorlova OY. A smoking-based carcinogenesis model for lung cancer risk prediction. Int J Cancer 2010 Dec 7. [Abstract]

Levy DT, Graham AL, Mabry PL, Abrams DB, Orleans CT. Modeling the impact of smoking-cessation treatment policies on quit rates. Am J Prev Med 2010 Mar;38(3 Suppl):S364-72. [Abstract]

Levy DT, Mabry PL, Graham AL, Abrams DB, Graham AL, Orleans CT. Reaching Healthy People 2010 by 2013: A SimSmoke Simulation. Am J Prev Med 2010 Mar;38(3 Suppl):S373-81. [Abstract]

Levy DT, Mabry P, Graham A., Orleans CT, Abrams D. Exploring Scenarios to Dramatically Reduce Smoking Prevalence: A Simulation Model of the Three-Part Cessation Process. Am J Public Health 2010 May 13. [Epub ahead of print] [Abstract]

Goldwasser DL, Kimmel M. Modeling excess lung cancer risk among screened arm participants in the Mayo Lung Project. Cancer 2010 Jan 1;116(1):122-31. [Abstract]


Zeller M, Hatsukami D. The Strategic Dialogue on Tobacco Harm Reduction: A Vision and Blueprint for Action in the United States. Tob Control. 2009 Aug;18(4):324-32. EPub 2009 Feb 24. [Abstract]


Deng L, Kimmel M, Foy M, Spitz M, Wei Q and Gorlova O. Estimation of the effects of smoking and DNA-repair capacity on coefficients of the carcinogenesis model of lung cancer. Int J Cancer 2008 Nov 11. [Abstract]

Levy DT, Tworek C, Hahn EJ, Davis RE. The Kentucky SimSmoke tobacco policy simulation model: reaching Healthy People 2010 goals through policy change. South Med J 2008 May;101(5):503-7. [Abstract]

McMahon PM, Kong CY, Johnson BE, Weinstein MC, Weeks JC, Kuntz KM, Shepard JO, Swensen SJ, Gazelle GS. Estimating long-term effectiveness of lung cancer screening in the Mayo CT Screening Study. Radiology 2008 Jul;248(1):278-87. [Abstract]

McMahon PM, Kong CY, Weinstein MC, Tramontano AC, Cipriano LE, Johnson BE, Weeks JC, Gazelle GS. Forthcoming. Adopting helical CT screening for lung cancer: potential health consequences over a fifteen-year period. Cancer 2008 Dec 15;113(12):3440-9. [Abstract]

Meza R, Hazelton WD, Colditz GA, Moolgavkar SH. Analysis of lung cancer incidence in the nurses' health and the health professionals' follow-up studies using a multistage carcinogenesis model. Cancer Causes Control Apr 2008;19(3):317-28. [Abstract]


Levy DT. The role of public policies in reducing smoking prevalence: results from the SimSmoke tobacco policy simulation model. In: Bonnie RJ, Stratton K, Wallace RB, editors. Committee on Reducing Tobacco Use: Strategies, Barriers, and Consequences, Ending the Tobacco Problem: A Blueprint for the Nation. Washington, D.C.: Institute of Medicine. 2007. p. 578-598. [Full Text]

Levy DT, Hyland A, Higbee C, Remer L, Compton C. The role of public policies in reducing smoking prevalence in California: results from the California tobacco policy simulation model. Health Policy 2007 Jul;82(2):167-85. [Abstract]

Levy DT, Mumford EA, Gerlowski DA. Examining trends in quantity smoked. Nicotine Tob Res 2007 Dec;9(12):1287-96. [Abstract]

Levy DT, Ross H, Powell L, Bauer J, Lee HR. The role of public policies in reducing smoking prevalence in Arizona: results from the Arizona tobacco policy simulation model. J Public Health Manag Pract 2007 Jan-Feb;13(1):59-67. [Abstract]

Marciniak-Czochra A, Kimmel M. Modelling of early lung cancer progression: influence of growth factor production and cooperation between partially transformed cells. Math Models Methods Appl Sci 2007;17(Suppl):1693-719.


Holford TR. Approaches to fitting age-period-cohort models with unequal intervals. Stat Med 2006 Mar 30;25(6):997-93. [Abstract]

Levy DT, Bauer JE, Lee HR. Simulation modeling and tobacco control: creating more robust public health policies. Am J Public Health 2006 Mar;96(3):494-8. [Abstract]

Levy DT, Mumford EA, Compton C. Tobacco control policies and smoking in a population of low education women, 1992-2002. J Epidemiol Community Health 2006 Sep;60 Suppl 2:20-6. [Abstract]


Clements MS, Armstrong BK, Moolgavkar SH. Lung cancer rate predictions using generalized additive models. Biostat 2005 Oct;6(4):576-89. Epub 2005 Apr 28. [Abstract]

Gorlova O, Peng B, Yankelevitz D, Henschke C, Kimmel M. Estimating the growth rates of primary lung tumours from samples with missing measurements. Stat Med 2005 Apr 15;24(7):1117-34. [Abstract]

Hazelton WD, Clements MS, Moolgavkar SH. Multistage carcinogenesis and lung cancer mortality in three cohorts. Cancer Epidemiol Biomarkers Prev 2005 May;14(5):1171-81. [Abstract]

Kimmel M, Gorlova O and Henschke CI. Modeling lung cancer screening. Chapter 10, in: Edler L and Kitsos C, editors. Recent Advances in Quantitative Methods in Cancer and Human Health Risk Assessment. New York: Wiley; 2005. p. 161-76. [Summary]

Levy D, Mumford E, Cummings M, Gilpin B, Giovino G, Hyland A, Sweanor D, Warner K. The potential impact of a low-nitrosamine smokeless tobacco product on cigarette smoking in the United States: Estimates of a panel of experts. Addict Behav 2006 Jul;31(7):1190-200. Epub 2005 Oct 26. [Abstract]

Levy DT, Nikolayev L, Mumford EA. Recent trends in smoking and the role of public policies: results from the SimSmoke Tobacco Control Policy Simulation Model. Addiction 2005;10(10):1526-37. [Abstract]

Levy DT, Nikolayev L, Mumford EA, Compton C. The Healthy People 2010 smoking prevalence and tobacco control objectives: results from the SimSmoke tobacco control policy simulation model (United States). Cancer Causes Control 2005 May;16(4):359-71. [Abstract]


Feuer EJ, Boer R, Holford TR. Developing and comparing population models for the early detection of cancer. Stat Meth Med Res 2004 Dec;13:419-20.

Levy DT, Mumford EA, Cummings KM, Gilpin EA, Giovino G, Hyland A, Sweanor D, Warner KE. The relative risks of a low-nitrosamine smokeless tobacco product compared with smoking cigarettes: estimates of a panel of experts. Cancer Epidemiol Biomarkers Prev 2004 Dec;13(12):2035-42. [Abstract]


Gorlova OY, Amos C, Henschke C, Lei L, Spitz M, Wei Q, Wu X, Kimmel M. Genetic susceptibility for lung cancer: interactions with gender and smoking history and impact on early detection policies. Hum Hered 2003;56:139-45. [Abstract]


Gregori G, Hanin LG, Luebeck G, Moolgavkar S, Yakovlev A. Testing goodness of fit for stochastic models of carcinogenesis. Math Biosci 2002 Jan;175(1):13-29. [Abstract]

Levy DT, Chaloupka F, Gitchell J, Mendez D, Warner KE. The use of simulation models for the surveillance, justification and understanding of tobacco control policies. Health Care Manag Sci Apr 2002;5(2):113-20. [Abstract]

Return to top

Prostate Working Group


Etzioni R, Mucci LA, Chen S, Johansson JE, Fall K, Adami HO. Increasing use of radical prostatectomy for non-lethal prostate cancer in Sweden. Clin Cancer Res 2012 Aug 27. [Epub ahead of print] [Abstract]

Xia J, Trock BJ, Cooperberg MR, Gulati R, Zeliadt SB, Gore JL, Lin DW, Carroll PR, Carter HB, Etzioni R. Prostate Cancer Mortality following Active Surveillance versus Immediate Radical Prostatectomy. Clin Cancer Res 2012 Oct 1;18(19):5471-5478. [Abstract]


Gulati R, Mariotto AB, Chen S, Gore JL, Etzioni R. Long-term projections of the harm-benefit trade-off in prostate cancer screening are more favorable than previous short-term estimates. J Clin Epidemiol 2011 Dec;64(12):1412-7. [Abstract]

Gulati R, Wever EM, Tsodikov A, Penson DF, Inoue LY, Katcher J, Lee SY, Heijnsdijk EA, Draisma G, de Koning HJ, Etzioni R. What if i don't treat my PSA-detected prostate cancer? Answers from three natural history models. Cancer Epidemiol Biomarkers Prev 2011 May;20(5):740-50. [Abstract]

Wever EM, Draisma G, Heijnsdijk EA, de Koning HJ. How does early detection by screening affect disease progression? Modeling estimated benefits in prostate cancer screening. Med Decis Making 2011 Jul-Aug;31(4):550-8. [Abstract]


Wever EM, Draisma G, Heijnsdijk EAM, MJ Roobol MJ, Boer R, Otto SJ, de Koning HJ. Prostate-specific antigen screening in the United States vs in the European Randomized Study of Screening for Prostate Cancer – Rotterdam. J Natl Cancer Inst 2010;02(5):352–355. [Abstract]


Draisma G, Etzioni R, Tsodikov A, Mariotto A, Wever E, Gulati R, Feuer E, de Koning H. Lead time and overdiagnosis in prostate-specific antigen screening: importance of methods and context. J Natl Cancer Inst 2009; 101(6):374–383. [Abstract]

Etzioni R, Gulati R, Mariotto AB. Overview of prostate cancer trends in the era of PSA screening. In: Ankerst DP, Tangen CM, Thompson IM, editors. Prostate Cancer screening. 2nd ed. Humana Press; 2009. p. 3-14.

Fesinmeyer MD, Gulati R, Zeliadt S, Weiss N, Kristal AR, Etzioni R. Effect of population trends in body mass index on prostate cancer incidence and mortality in the United States. Cancer Epidemiol Biomarkers Prev 2009 Mar;18(3):808-15. [Abstract]


Etzioni R, Feuer E. Studies of prostate-cancer mortality: caution advised. Lancet Oncol 2008 May;9(5):407-9. [Abstract]

Etzioni R, Gulati R, Falcon S, Penson DF. Impact of PSA screening on the incidence of advanced stage prostate cancer in the U.S.: a surveillance modeling approach. Med Decis Making 2008 Mar 4;28(3):323-31. [Abstract]

Etzioni R, Tsodikov A, Mariotto A, Szabo A, Falcon S, Wegelin J, diTommaso D, Karnofski K, Gulati R, Penson DF, Feuer EJ. Quantifying the role of PSA screening in the U.S. prostate cancer mortality decline. Cancer Causes Control 2008 Mar;19(2):175-81. [Abstract]

Inoue LY, Etzioni R, Morrell C, Muller P. Modeling disease progression with longitudinal markers. J Am Stat Assoc 2008 Mar;103(481):259-70. [Abstract]

Telesca D, Etzioni R, Gulati R. Estimating lead time and overdiagnosis associated with PSA screening from prostate cancer incidence trends. Biometrics 2008 Mar;64(1):10-9. [Abstract]

Tsodikov A, Chefo S. Generalized sef-consistency: multinomial logit model and Poisson likelihood. J Stat Plan Inference 2008;138(8):2380-97. [Abstract]


Mariotto AB, Etzioni R, Krapcho M, Feuer EJ. Reconstructing prostate-specific antigen (PSA) testing patterns among black and white men in the U.S. from Medicare claims and the National Health Interview Survey. Cancer 2007 Mar 19;109(9):1877-86. [Abstract]

Tsodikov A, Garibotti G. Profile information matrix for nonlinear transformation models. Lifetime Data Anal 2007 Mar;13(1):139-59. [Abstract]

Zeliadt SB, Etzioni R, Ramsey SD, Penson DF, Potosky AL. Trends in treatment costs for localized prostate cancer: the healthy screenee effect. Med Care 2007 Feb; 45(2):154-9. [Abstract]


Draisma G, Postma R, Schröder FH, van der Kwast TH, de Koning HJ. Gleason score, age and screening: modeling dedifferentiation in prostate cancer. Int J Cancer 2006 Nov 15;119(10):2366-71. [Abstract]

Tsodikov A, Szabo A, Wegelin J. A population model of prostate cancer incidence. Stat Med 2006 Aug 30;25(16):2846-66. [Abstract]

Zeliadt SB, Potosky AL, Penson DF, Etzioni R. Survival benefit associated with adjuvant androgen deprivation therapy combined with radiotherapy for high- and low-risk patients with nonmetastatic prostate cancer. Int J Radiat Oncol Biol Phys 2006 Oct 1;66(2):395-402. [Abstract]


Broët P, Tsodikov A. De Rycke Y, Moreau T. Two-sample statistics for testing the equality of survival functions against improper semi-parametric accelerated failure time alternatives: An application to the analysis of a breast cancer clinical trial. Lifetime Data Anal 2004;10(2):103-20. [Abstract]

Feuer EJ, Etzioni R, Cronin KA, Mariotto A. The use of modeling to understand the impact of screening on U.S. mortality: examples from mammography and PSA testing. Stat Methods Med Res 2004 Dec;13(6):421-42. [Abstract]

Inoue LY, Etzioni R, Slate EH, Morrell C, Penson DF. Combining logitudinal studies of PSA. Biostat 2004;5:483-500. [Abstract]

Shaw PA, Etzioni R, Zeliadt SB, Mariotto A, Karnofski K, Penson DF, Weiss NS, Feuer EJ. An ecologic study of prostate-specific antigen screening and prostate cancer mortality in nine geographic areas of the United States. Am J Epidemiol 2004 Dec 1;160(11):1059-69. [Abstract]

Zeliadt SB, Potosky AL, Etzioni R, Ramsey SD, Penson DF. Racial disparity in primary and adjuvant treatment for nonmetastatic prostate cancer: SEER-Medicare trends 1991 to 1999. Urology 2004 Dec;64(6):1171-6. [Abstract]


Tsodikov A. Semiparametric models: a generalized self-consistency approach. J R Stat Soc Ser B Stat Methodol 2003 Aug;65(3):759-74. [Abstract]

Tsodikov AD, Ibrahim JG,Yakovlev AY. Estimating cure rates from survival data: an alternative to two-component mixture models. J Amer Statist Assoc 2003;98:1063-78. [Abstract]

Zeliadt SB, Penson DF, Albertsen PC, Concato J, Etzioni R. Race independently predicts prostate specific antigen testing frequency following a prostate carcinoma diagnosis. Cancer 2003 Aug 1;98(3):496-503. [Abstract]


Etzioni R, Berry KM, Legler J, Shaw P. Prostate-specific antigen testing in black and white men: an analysis of Medicare claims from 1991-1998. Urology 2002 Feb;59(2):251-255. [Abstract]

Etzioni R, Penson DF, Legler JM, di Tommaso D, Boer R, Gann PH, Feuer EJ. Overdiagnosis due to prostate-specific antigen screening: lessons from U.S. prostate cancer incidence trends. J Natl Cancer Inst 2002 Jul 3;94(13):981-90. [Abstract]

McCulloch CE, Lin H, Slate EH, Turnbull BW. Discovering subpopulation structure with latent class mixed models. Stat Med 2002 Feb 15;21(3):417-29. [Abstract]

Return to top