Literature DB >> 15173213

Benefits and costs of interventions to improve breast cancer outcomes in African American women.

Jeanne S Mandelblatt1, Clyde B Schechter, K Robin Yabroff, William Lawrence, James Dignam, Peter Muennig, Yoko Chavez, Jennifer Cullen, Marianne Fahs.   

Abstract

PURPOSE: Historically, African American women have experienced higher breast cancer mortality than white women, despite lower incidence. Our objective was to evaluate whether costs of increasing rates of screening or application of intensive treatment will be off-set by survival benefits for African American women.
METHODS: We use a stochastic simulation model of the natural history of breast cancer to evaluate the incremental societal costs and benefits of status quo versus targeted biennial screening or treatment improvements among African Americans 40 years of age and older. Main outcome measures were number of mammograms, stage, all-cause mortality, and discounted costs per life year saved (LYS).
RESULTS: At the current screening rate of 76%, there is little incremental benefit associated with further increasing screening, and the costs are high: 124,053 US dollars and 124,217 US dollars per LYS for lay health worker and patient reminder interventions, respectively, compared with the status quo. Using reminders would cost 51,537 US dollars per LYS if targeted to virtually unscreened women or 78,130 US dollars per LYS if targeted to women with a two-fold increase in baseline risk. If all patients received the most intensive treatment recommended, costs increase but deaths decrease, for a cost of 52,678 US dollars per LYS. Investments of up to 6,000 US dollars per breast cancer patient could be used to enhance treatment and still yield cost-effectiveness ratios of less than 75,000 US dollars per LYS.
CONCLUSION: Except in pockets of unscreened or high-risk women, further investments in interventions to increase screening are unlikely to be an efficient use of resources. Ensuring that African American women receive intensive treatment seems to be the most cost-effective approach to decreasing the disproportionate mortality experienced by this population.

Entities:  

Mesh:

Year:  2004        PMID: 15173213     DOI: 10.1200/JCO.2004.05.009

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   44.544


  20 in total

1.  Risk-specific optimal cancer screening schedules: an application to breast cancer early detection.

Authors:  Charlotte Hsieh Ahern; Yi Cheng; Yu Shen
Journal:  Stat Biosci       Date:  2011-12

2.  The Italian health surveillance (SiVeAS) prioritization approach to reduce chronic disease risk factors.

Authors:  Eduardo J Simoes; Sergio Mariotti; Alessandra Rossi; Alicia Heim; Felipe Lobello; Ali H Mokdad; Emanuele Scafato
Journal:  Int J Public Health       Date:  2012-02-14       Impact factor: 3.380

3.  Computational modeling and multilevel cancer control interventions.

Authors:  Joseph P Morrissey; Kristen Hassmiller Lich; Rebecca Anhang Price; Jeanne Mandelblatt
Journal:  J Natl Cancer Inst Monogr       Date:  2012-05

Review 4.  Calibration methods used in cancer simulation models and suggested reporting guidelines.

Authors:  Natasha K Stout; Amy B Knudsen; Chung Yin Kong; Pamela M McMahon; G Scott Gazelle
Journal:  Pharmacoeconomics       Date:  2009       Impact factor: 4.981

5.  Breast Cancer Risk Assessment Among Low-Income Women of Color in Primary Care: A Pilot Study.

Authors:  Emily E Anderson; Silvia Tejeda; Kimberly Childers; Melinda R Stolley; Richard B Warnecke; Kent F Hoskins
Journal:  J Oncol Pract       Date:  2015-06-02       Impact factor: 3.840

6.  Are breast cancer navigation programs cost-effective? Evidence from the Chicago Cancer Navigation Project.

Authors:  Talar W Markossian; Elizabeth A Calhoun
Journal:  Health Policy       Date:  2010-08-04       Impact factor: 2.980

7.  Improving Breast Cancer Outcomes Through Patient Navigation.

Authors:  Lisa C Richardson
Journal:  J Womens Health (Larchmt)       Date:  2016-11-21       Impact factor: 2.681

8.  Benefits and harms of mammography screening after age 74 years: model estimates of overdiagnosis.

Authors:  Nicolien T van Ravesteyn; Natasha K Stout; Clyde B Schechter; Eveline A M Heijnsdijk; Oguzhan Alagoz; Amy Trentham-Dietz; Jeanne S Mandelblatt; Harry J de Koning
Journal:  J Natl Cancer Inst       Date:  2015-05-06       Impact factor: 13.506

9.  Structure, Function, and Applications of the Georgetown-Einstein (GE) Breast Cancer Simulation Model.

Authors:  Clyde B Schechter; Aimee M Near; Jinani Jayasekera; Young Chandler; Jeanne S Mandelblatt
Journal:  Med Decis Making       Date:  2018-04       Impact factor: 2.583

10.  Factors influencing breast cancer screening in low-income African Americans in Tennessee.

Authors:  Kushal Patel; Mohamed Kanu; Jianguo Liu; Brea Bond; Elizabeth Brown; Elizabeth Williams; Rosemary Theriot; Stephanie Bailey; Maureen Sanderson; Margaret Hargreaves
Journal:  J Community Health       Date:  2014-10
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.