© 2005 Oxford University Press
COMMENTARY |
Cancer Risk Prediction Models: A Workshop on Development, Evaluation, and Application
Affiliations of authors: Division of Cancer Control and Population Sciences (ANF, DS, RB-B) and Division of Cancer Epidemiology and Genetics (MHG, PH, RMP), National Cancer Institute, Bethesda, MD; Department of Epidemiology, Harvard School of Public Health, Boston, MA (GAC)
Correspondence to: Andrew N. Freedman, PhD, National Cancer Institute, National Institutes of Health, EPN 4005 MSC 7344, 6130 Executive Blvd., Bethesda, MD 20892–7344 (e-mail: Andrew_Freedman{at}nih.gov).
Cancer researchers, clinicians, and the public are increasingly interested in statistical models designed to predict the occurrence of cancer. As the number and sophistication of cancer risk prediction models have grown, so too has interest in ensuring that they are appropriately applied, correctly developed, and rigorously evaluated. On May 20–21, 2004, the National Cancer Institute sponsored a workshop in which experts identified strengths and limitations of cancer and genetic susceptibility prediction models that were currently in use and under development and explored methodologic issues related to their development, evaluation, and validation. Participants also identified research priorities and resources in the areas of 1) revising existing breast cancer risk assessment models and developing new models, 2) encouraging the development of new risk models, 3) obtaining data to develop more accurate risk models, 4) supporting validation mechanisms and resources, 5) strengthening model development efforts and encouraging coordination, and 6) promoting effective cancer risk communication and decision-making.
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  G. A. Colditz and D. M. Winn Criteria for the Evaluation of Large Cohort Studies: An Application to the Nurses' Health Study J Natl Cancer Inst, July 2, 2008; 100(13): 918 - 925. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. J. Wang, C. D. Fuller, J.-S. Kim, D. F. Sittig, C. R. Thomas Jr, and P. M. Ravdin Prediction Model for Estimating the Survival Benefit of Adjuvant Radiotherapy for Gallbladder Cancer J. Clin. Oncol., May 1, 2008; 26(13): 2112 - 2117. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. Iasonos, D. Schrag, G. V. Raj, and K. S. Panageas How To Build and Interpret a Nomogram for Cancer Prognosis J. Clin. Oncol., March 10, 2008; 26(8): 1364 - 1370. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. A. Tice, S. R. Cummings, R. Smith-Bindman, L. Ichikawa, W. E. Barlow, and K. Kerlikowske Using Clinical Factors and Mammographic Breast Density to Estimate Breast Cancer Risk: Development and Validation of a New Predictive Model Ann Intern Med, March 4, 2008; 148(5): 337 - 347. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. T. Chlebowski, G. L. Anderson, D. S. Lane, A. K. Aragaki, T. Rohan, S. Yasmeen, G. Sarto, C. A. Rosenberg, F. A. Hubbell, and For the Women's Health Initiative Investigators Predicting Risk of Breast Cancer in Postmenopausal Women by Hormone Receptor Status J Natl Cancer Inst, November 21, 2007; 99(22): 1695 - 1705. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
X. Wu, J. Lin, H. B. Grossman, M. Huang, J. Gu, C. J. Etzel, C. I. Amos, C. P. Dinney, and M. R. Spitz Projecting Individualized Probabilities of Developing Bladder Cancer in White Individuals J. Clin. Oncol., November 1, 2007; 25(31): 4974 - 4981. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 R. J Santen, N. F Boyd, R. T Chlebowski, S. Cummings, J. Cuzick, M. Dowsett, D. Easton, J. F Forbes, T. Key, S. E Hankinson, et al. Critical assessment of new risk factors for breast cancer: considerations for development of an improved risk prediction model Endocr. Relat. Cancer, June 1, 2007; 14(2): 169 - 187. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. R. Spitz, W. K. Hong, C. I. Amos, X. Wu, M. B. Schabath, Q. Dong, S. Shete, and C. J. Etzel A Risk Model for Prediction of Lung Cancer J Natl Cancer Inst, May 2, 2007; 99(9): 715 - 726. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
W. Wang, S. Chen, K. A. Brune, R. H. Hruban, G. Parmigiani, and A. P. Klein PancPRO: Risk Assessment for Individuals With a Family History of Pancreatic Cancer J. Clin. Oncol., April 10, 2007; 25(11): 1417 - 1422. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. G. Elmore and S. W. Fletcher The Risk of Cancer Risk Prediction: "What Is My Risk of Getting Breast Cancer?" J Natl Cancer Inst, December 6, 2006; 98(23): 1673 - 1675. [Full Text] [PDF]
|
|
|
|
|
|
A. Decarli, S. Calza, G. Masala, C. Specchia, D. Palli, and M. H. Gail Gail Model for Prediction of Absolute Risk of Invasive Breast Cancer: Independent Evaluation in the Florence-European Prospective Investigation Into Cancer and Nutrition Cohort J Natl Cancer Inst, December 6, 2006; 98(23): 1686 - 1693. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. J. Vickers and E. B. Elkin Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making, November 1, 2006; 26(6): 565 - 574. [Abstract] [PDF]
|
|
|
|
|
|
W. E. Barlow, E. White, R. Ballard-Barbash, P. M. Vacek, L. Titus-Ernstoff, P. A. Carney, J. A. Tice, D. S. M. Buist, B. M. Geller, R. Rosenberg, et al. Prospective breast cancer risk prediction model for women undergoing screening mammography. J Natl Cancer Inst, September 6, 2006; 98(17): 1204 - 1214. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
F. L. Meyskens Jr and D. F. Ransohoff Predicting Risk for the Appearance of Melanoma J. Clin. Oncol., August 1, 2006; 24(22): 3522 - 3523. [Full Text] [PDF]
|
|
|
|
 |
|
 G. J. Kelloff, S. M. Lippman, A. J. Dannenberg, C. C. Sigman, H. L. Pearce, B. J. Reid, E. Szabo, V. C. Jordan, M. R. Spitz, G. B. Mills, et al. Progress in Chemoprevention Drug Development: The Promise of Molecular Biomarkers for Prevention of Intraepithelial Neoplasia and Cancer--A Plan to Move Forward Clin. Cancer Res., June 15, 2006; 12(12): 3661 - 3697. [Abstract] [Full Text] [PDF]
|
|