Literature DB >> 10491430

Validation studies for models projecting the risk of invasive and total breast cancer incidence.

J P Costantino1, M H Gail, D Pee, S Anderson, C K Redmond, J Benichou, H S Wieand.   

Abstract

BACKGROUND: In 1989, Gail and colleagues developed a model for estimating the risk of breast cancer in women participating in a program of annual mammographic screening (designated herein as model 1). A modification of this model to project the absolute risk of developing only invasive breast cancer is referred to herein as model 2. We assessed the validity of both models by employing data from women enrolled in the Breast Cancer Prevention Trial.
METHODS: We used data from 5969 white women who were at least 35 years of age and without a history of breast cancer. These women were in the placebo arm of the trial and were screened annually. The average follow-up period was 48.4 months. We compared the observed number of breast cancers with the predicted numbers from the models.
RESULTS: In terms of absolute risk, the ratios of total expected to observed numbers of cancers (95% confidence intervals [CIs]) were 0.84 (0. 73-0.97) for model 1 and 1.03 (0.88-1.21) for model 2, respectively. Within the age groups of 49 years or less, 50-59 years, and 60 years or more, the ratios of expected to observed numbers of breast cancers (95% CIs) for model 1 were 0.91 (0.73-1.14), 0.96 (0.73-1. 28), and 0.66 (0.52-0.86), respectively. Thus, model 1 underestimated breast cancer risk in women more than 59 years of age. For model 2, the risk ratios (95% CIs) were 0.93 (0.72-1.22), 1.13 (0.83-1.55), and 1.05 (0.80-1.41), respectively. Both models exhibited a tendency to overestimate risk for women classified in the higher quintiles of predicted 5-year risk and to underestimate risk for those in the lower quintiles of the same.
CONCLUSION: Despite some limitations, these methods provide useful information on breast cancer risk for women who plan to participate in an annual mammographic screening program.

Entities:  

Mesh:

Year:  1999        PMID: 10491430     DOI: 10.1093/jnci/91.18.1541

Source DB:  PubMed          Journal:  J Natl Cancer Inst        ISSN: 0027-8874            Impact factor:   13.506


  229 in total

1.  Evaluating breast cancer risk projections for Hispanic women.

Authors:  Matthew P Banegas; Mitchell H Gail; Andrea LaCroix; Beti Thompson; Maria Elena Martinez; Jean Wactawski-Wende; Esther M John; F Allan Hubbell; Shagufta Yasmeen; Hormuzd A Katki
Journal:  Breast Cancer Res Treat       Date:  2011-12-07       Impact factor: 4.872

Review 2.  Clinical and epidemiological issues in mammographic density.

Authors:  Valentina Assi; Jane Warwick; Jack Cuzick; Stephen W Duffy
Journal:  Nat Rev Clin Oncol       Date:  2011-12-06       Impact factor: 66.675

Review 3.  Genetics for the general internist.

Authors:  Christina M Laukaitis
Journal:  Am J Med       Date:  2011-11-11       Impact factor: 4.965

Review 4.  Ductal lavage in the screening of high-risk women.

Authors:  Patrick J Kenney; Margarett C Ellison
Journal:  Curr Oncol Rep       Date:  2004-01       Impact factor: 5.075

5.  A novel automated mammographic density measure and breast cancer risk.

Authors:  John J Heine; Christopher G Scott; Thomas A Sellers; Kathleen R Brandt; Daniel J Serie; Fang-Fang Wu; Marilyn J Morton; Beth A Schueler; Fergus J Couch; Janet E Olson; V Shane Pankratz; Celine M Vachon
Journal:  J Natl Cancer Inst       Date:  2012-07-03       Impact factor: 13.506

6.  Performance of common genetic variants in breast-cancer risk models.

Authors:  Sholom Wacholder; Patricia Hartge; Ross Prentice; Montserrat Garcia-Closas; Heather Spencer Feigelson; W Ryan Diver; Michael J Thun; David G Cox; Susan E Hankinson; Peter Kraft; Bernard Rosner; Christine D Berg; Louise A Brinton; Jolanta Lissowska; Mark E Sherman; Rowan Chlebowski; Charles Kooperberg; Rebecca D Jackson; Dennis W Buckman; Peter Hui; Ruth Pfeiffer; Kevin B Jacobs; Gilles D Thomas; Robert N Hoover; Mitchell H Gail; Stephen J Chanock; David J Hunter
Journal:  N Engl J Med       Date:  2010-03-18       Impact factor: 91.245

7.  Application of the Rosner-Colditz risk prediction model to estimate sexual orientation group disparities in breast cancer risk in a U.S. cohort of premenopausal women.

Authors:  S Bryn Austin; Mathew J Pazaris; Bernard Rosner; Deborah Bowen; Janet Rich-Edwards; Donna Spiegelman
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2012-10-03       Impact factor: 4.254

8.  Predictors of contralateral breast cancer in patients with unilateral breast cancer undergoing contralateral prophylactic mastectomy.

Authors:  Min Yi; Funda Meric-Bernstam; Lavinia P Middleton; Banu K Arun; Isabelle Bedrosian; Gildy V Babiera; Rosa F Hwang; Henry M Kuerer; Wei Yang; Kelly K Hunt
Journal:  Cancer       Date:  2009-03-01       Impact factor: 6.860

9.  A randomized trial of three videos that differ in the framing of information about mammography in women 40 to 49 years old.

Authors:  Carmen L Lewis; Michael P Pignone; Stacey L Sheridan; Stephen M Downs; Linda S Kinsinger
Journal:  J Gen Intern Med       Date:  2003-11       Impact factor: 5.128

10.  Acceptance and adherence to chemoprevention among women at increased risk of breast cancer.

Authors:  Richard G Roetzheim; Ji-Hyun Lee; William Fulp; Elizabeth Matos Gomez; Elissa Clayton; Sharon Tollin; Nazanin Khakpour; Christine Laronga; Marie Catherine Lee; John V Kiluk
Journal:  Breast       Date:  2014-12-06       Impact factor: 4.380

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.