Literature DB >> 25076829

Pursuing optimal thresholds to recommend breast biopsy by quantifying the value of tomosynthesis.

Yirong Wu1, Oguzhan Alagoz2, David J Vanness3, Amy Trentham-Dietz3, Elizabeth S Burnside1.   

Abstract

A 2% threshold has been traditionally used to recommend breast biopsy in mammography. We aim to characterize how the biopsy threshold varies to achieve the maximum expected utility (MEU) of tomosynthesis for breast cancer diagnosis. A cohort of 312 patients, imaged with standard full field digital mammography (FFDM) and digital breast tomosynthesis (DBT), was selected for a reader study. Fifteen readers interpreted each patient's images and estimated the probability of malignancy using two modes: FFDM versus FFDM + DBT. We generated receiver operator characteristic (ROC) curves with the probabilities for all readers combined. We found that FFDM+DBT provided improved accuracy and MEU compared with FFDM alone. When DBT was included in the diagnosis along with FFDM, the optimal biopsy threshold increased to 2.7% as compared with the 2% threshold for FFDM alone. While understanding the optimal threshold from a decision analytic standpoint will not help physicians improve their performance without additional guidance (e.g. decision support to reinforce this threshold), the discovery of this level does demonstrate the potential clinical improvements attainable with DBT. Specifically, DBT has the potential to lead to substantial improvements in breast cancer diagnosis since it could reduce the number of patients recommended for biopsy while preserving the maximal expected utility.

Entities:  

Keywords:  Breast Biopsy; Digital Breast Tomosynthesis; Expected Utility; Mammography; ROC Analysis

Year:  2014        PMID: 25076829      PMCID: PMC4112817          DOI: 10.1117/12.2042905

Source DB:  PubMed          Journal:  Proc SPIE Int Soc Opt Eng        ISSN: 0277-786X


  32 in total

1.  A comparison of C/B ratios from studies using receiver operating characteristic curve analysis.

Authors:  S B Cantor; C C Sun; G Tortolero-Luna; R Richards-Kortum; M Follen
Journal:  J Clin Epidemiol       Date:  1999-09       Impact factor: 6.437

2.  Multireader, multicase receiver operating characteristic analysis: an empirical comparison of five methods.

Authors:  Nancy A Obuchowski; Sergey V Beiden; Kevin S Berbaum; Stephen L Hillis; Hemant Ishwaran; Hae Hiang Song; Robert F Wagner
Journal:  Acad Radiol       Date:  2004-09       Impact factor: 3.173

3.  Reader variability in mammography and its implications for expected utility over the population of readers and cases.

Authors:  Robert F Wagner; Craig A Beam; Sergey V Beiden
Journal:  Med Decis Making       Date:  2004 Nov-Dec       Impact factor: 2.583

4.  Personalizing mammography by breast density and other risk factors for breast cancer: analysis of health benefits and cost-effectiveness.

Authors:  John T Schousboe; Karla Kerlikowske; Andrew Loh; Steven R Cummings
Journal:  Ann Intern Med       Date:  2011-07-05       Impact factor: 25.391

5.  Estimating the relative utility of screening mammography.

Authors:  Craig K Abbey; Miguel P Eckstein; John M Boone
Journal:  Med Decis Making       Date:  2013-01-07       Impact factor: 2.583

6.  Breast biopsy utilization: a population-based study.

Authors:  Karthik Ghosh; L Joseph Melton; Vera J Suman; Clive S Grant; Sylvester Sterioff; Kathy R Brandt; Charles Branch; Thomas A Sellers; Lynn C Hartmann
Journal:  Arch Intern Med       Date:  2005-07-25

Review 7.  Systematic review: the long-term effects of false-positive mammograms.

Authors:  Noel T Brewer; Talya Salz; Sarah E Lillie
Journal:  Ann Intern Med       Date:  2007-04-03       Impact factor: 25.391

8.  Tipping the balance of benefits and harms to favor screening mammography starting at age 40 years: a comparative modeling study of risk.

Authors:  Nicolien T van Ravesteyn; Diana L Miglioretti; Natasha K Stout; Sandra J Lee; Clyde B Schechter; Diana S M Buist; Hui Huang; Eveline A M Heijnsdijk; Amy Trentham-Dietz; Oguzhan Alagoz; Aimee M Near; Karla Kerlikowske; Heidi D Nelson; Jeanne S Mandelblatt; Harry J de Koning
Journal:  Ann Intern Med       Date:  2012-05-01       Impact factor: 25.391

9.  Revisiting the mammographic follow-up of BI-RADS category 3 lesions.

Authors:  Ximena Varas; José H Leborgne; Francisco Leborgne; Julieta Mezzera; Sylvia Jaumandreu; Felix Leborgne
Journal:  AJR Am J Roentgenol       Date:  2002-09       Impact factor: 3.959

Review 10.  Breast cancer risk-assessment models.

Authors:  D Gareth R Evans; Anthony Howell
Journal:  Breast Cancer Res       Date:  2007       Impact factor: 6.466

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  2 in total

1.  Developing a utility decision framework to evaluate predictive models in breast cancer risk estimation.

Authors:  Yirong Wu; Craig K Abbey; Xianqiao Chen; Jie Liu; David C Page; Oguzhan Alagoz; Peggy Peissig; Adedayo A Onitilo; Elizabeth S Burnside
Journal:  J Med Imaging (Bellingham)       Date:  2015-08-17

2.  Developing a clinical utility framework to evaluate prediction models in radiogenomics.

Authors:  Yirong Wu; Jie Liu; Alejandro Munoz Del Rio; David C Page; Oguzhan Alagoz; Peggy Peissig; Adedayo A Onitilo; Elizabeth S Burnside
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2015-03-17
  2 in total

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