Literature DB >> 23588746

Short-term outcomes of screening mammography using computer-aided detection: a population-based study of medicare enrollees.

Joshua J Fenton1, Guibo Xing, Joann G Elmore, Heejung Bang, Steven L Chen, Karen K Lindfors, Laura-Mae Baldwin.   

Abstract

BACKGROUND: Computer-aided detection (CAD) has rapidly diffused into screening mammography practice despite limited and conflicting data on its clinical effect.
OBJECTIVE: To determine associations between CAD use during screening mammography and the incidence of ductal carcinoma in situ (DCIS) and invasive breast cancer, invasive cancer stage, and diagnostic testing.
DESIGN: Retrospective cohort study.
SETTING: Medicare program. PARTICIPANTS: Women aged 67 to 89 years having screening mammography between 2001 and 2006 in U.S. SEER (Surveillance, Epidemiology and End Results) regions (409 459 mammograms from 163 099 women). MEASUREMENTS: Incident DCIS and invasive breast cancer within 1 year after mammography, invasive cancer stage, and diagnostic testing within 90 days after screening among women without breast cancer.
RESULTS: From 2001 to 2006, CAD prevalence increased from 3.6% to 60.5%. Use of CAD was associated with greater DCIS incidence (adjusted odds ratio [OR], 1.17 [95% CI, 1.11 to 1.23]) but no difference in invasive breast cancer incidence (adjusted OR, 1.00 [CI, 0.97 to 1.03]). Among women with invasive cancer, CAD was associated with greater likelihood of stage I to II versus III to IV cancer (adjusted OR, 1.27 [CI, 1.14 to 1.41]). In women without breast cancer, CAD was associated with increased odds of diagnostic mammography (adjusted OR, 1.28 [CI, 1.27 to 1.29]), breast ultrasonography (adjusted OR, 1.07 [CI, 1.06 to 1.09]), and breast biopsy (adjusted OR, 1.10 [CI, 1.08 to 1.12]). LIMITATION: Short follow-up for cancer stage, potential unmeasured confounding, and uncertain generalizability to younger women.
CONCLUSION: Use of CAD during screening mammography among Medicare enrollees is associated with increased DCIS incidence, the diagnosis of invasive breast cancer at earlier stages, and increased diagnostic testing among women without breast cancer. PRIMARY FUNDING SOURCE: Center for Healthcare Policy and Research, University of California, Davis.

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Year:  2013        PMID: 23588746      PMCID: PMC3772716          DOI: 10.7326/0003-4819-158-8-201304160-00002

Source DB:  PubMed          Journal:  Ann Intern Med        ISSN: 0003-4819            Impact factor:   25.391


  40 in total

Review 1.  Diffusion of computer-aided mammography after mandated Medicare coverage.

Authors:  Joshua J Fenton; Susan Bartlett Foote; Pamela Green; Laura-Mae Baldwin
Journal:  Arch Intern Med       Date:  2010-06-14

2.  How widely is computer-aided detection used in screening and diagnostic mammography?

Authors:  Vijay M Rao; David C Levin; Laurence Parker; Barbara Cavanaugh; Andrea J Frangos; Jonathan H Sunshine
Journal:  J Am Coll Radiol       Date:  2010-10       Impact factor: 5.532

3.  Comorbidities and mammography use interact to explain racial/ethnic disparities in breast cancer stage at diagnosis.

Authors:  Shagufta Yasmeen; Guibo Xing; Cyllene Morris; Rowan T Chlebowski; Patrick S Romano
Journal:  Cancer       Date:  2011-01-18       Impact factor: 6.860

Review 4.  Advanced breast cancer and breast cancer mortality in randomized controlled trials on mammography screening.

Authors:  Philippe Autier; Clarisse Héry; Jari Haukka; Mathieu Boniol; Graham Byrnes
Journal:  J Clin Oncol       Date:  2009-11-02       Impact factor: 44.544

5.  Internal validation of procedure codes on Medicare claims for digital mammograms and computer-aided detection.

Authors:  Joshua J Fenton; Pamela Green; Laura-Mae Baldwin
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2009-08       Impact factor: 4.254

6.  Effectiveness of computer-aided detection in community mammography practice.

Authors:  Joshua J Fenton; Linn Abraham; Stephen H Taplin; Berta M Geller; Patricia A Carney; Carl D'Orsi; Joann G Elmore; William E Barlow
Journal:  J Natl Cancer Inst       Date:  2011-07-27       Impact factor: 13.506

7.  When radiologists perform best: the learning curve in screening mammogram interpretation.

Authors:  Diana L Miglioretti; Charlotte C Gard; Patricia A Carney; Tracy L Onega; Diana S M Buist; Edward A Sickles; Karla Kerlikowske; Robert D Rosenberg; Bonnie C Yankaskas; Berta M Geller; Joann G Elmore
Journal:  Radiology       Date:  2009-09-29       Impact factor: 11.105

8.  Effects of mammography screening under different screening schedules: model estimates of potential benefits and harms.

Authors:  Jeanne S Mandelblatt; Kathleen A Cronin; Stephanie Bailey; Donald A Berry; Harry J de Koning; Gerrit Draisma; Hui Huang; Sandra J Lee; Mark Munsell; Sylvia K Plevritis; Peter Ravdin; Clyde B Schechter; Bronislava Sigal; Michael A Stoto; Natasha K Stout; Nicolien T van Ravesteyn; John Venier; Marvin Zelen; Eric J Feuer
Journal:  Ann Intern Med       Date:  2009-11-17       Impact factor: 25.391

9.  Breast cancer screening results 5 years after introduction of digital mammography in a population-based screening program.

Authors:  Nico Karssemeijer; Adriana M Bluekens; David Beijerinck; Jan J Deurenberg; Matthijs Beekman; Roelant Visser; Ruben van Engen; Annemieke Bartels-Kortland; Mireille J Broeders
Journal:  Radiology       Date:  2009-07-31       Impact factor: 11.105

10.  Single reading with computer-aided detection for screening mammography.

Authors:  Fiona J Gilbert; Susan M Astley; Maureen G C Gillan; Olorunsola F Agbaje; Matthew G Wallis; Jonathan James; Caroline R M Boggis; Stephen W Duffy
Journal:  N Engl J Med       Date:  2008-10-01       Impact factor: 91.245

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  23 in total

1.  Collaborative Modeling of the Benefits and Harms Associated With Different U.S. Breast Cancer Screening Strategies.

Authors:  Jeanne S Mandelblatt; Natasha K Stout; Clyde B Schechter; Jeroen J van den Broek; Diana L Miglioretti; Martin Krapcho; Amy Trentham-Dietz; Diego Munoz; Sandra J Lee; Donald A Berry; Nicolien T van Ravesteyn; Oguzhan Alagoz; Karla Kerlikowske; Anna N A Tosteson; Aimee M Near; Amanda Hoeffken; Yaojen Chang; Eveline A Heijnsdijk; Gary Chisholm; Xuelin Huang; Hui Huang; Mehmet Ali Ergun; Ronald Gangnon; Brian L Sprague; Sylvia Plevritis; Eric Feuer; Harry J de Koning; Kathleen A Cronin
Journal:  Ann Intern Med       Date:  2016-01-12       Impact factor: 25.391

2.  Evaluation of computer-aided detection and diagnosis systems.

Authors:  Nicholas Petrick; Berkman Sahiner; Samuel G Armato; Alberto Bert; Loredana Correale; Silvia Delsanto; Matthew T Freedman; David Fryd; David Gur; Lubomir Hadjiiski; Zhimin Huo; Yulei Jiang; Lia Morra; Sophie Paquerault; Vikas Raykar; Frank Samuelson; Ronald M Summers; Georgia Tourassi; Hiroyuki Yoshida; Bin Zheng; Chuan Zhou; Heang-Ping Chan
Journal:  Med Phys       Date:  2013-08       Impact factor: 4.071

Review 3.  Breast cancer screening: an evidence-based update.

Authors:  Mackenzie S Fuller; Christoph I Lee; Joann G Elmore
Journal:  Med Clin North Am       Date:  2015-03-05       Impact factor: 5.456

4.  Effect of radiologists' diagnostic work-up volume on interpretive performance.

Authors:  Diana S M Buist; Melissa L Anderson; Robert A Smith; Patricia A Carney; Diana L Miglioretti; Barbara S Monsees; Edward A Sickles; Stephen H Taplin; Berta M Geller; Bonnie C Yankaskas; Tracy L Onega
Journal:  Radiology       Date:  2014-06-24       Impact factor: 11.105

5.  Computer-aided detection in mammography: downstream effect on diagnostic testing, ductal carcinoma in situ treatment, and costs.

Authors:  Joshua J Fenton; Christoph I Lee; Guibo Xing; Laura-Mae Baldwin; Joann G Elmore
Journal:  JAMA Intern Med       Date:  2014-12       Impact factor: 21.873

6.  Computerized detection of breast cancer on automated breast ultrasound imaging of women with dense breasts.

Authors:  Karen Drukker; Charlene A Sennett; Maryellen L Giger
Journal:  Med Phys       Date:  2014-01       Impact factor: 4.071

7.  Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study.

Authors:  Daniele Catanzaro; Stanley E Shackney; Alejandro A Schaffer; Russell Schwartz
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2015-09-04       Impact factor: 3.710

8.  Development and validation of algorithms to differentiate ductal carcinoma in situ from invasive breast cancer within administrative claims data.

Authors:  Jacqueline M Hirth; Sandra S Hatch; Yu-Li Lin; Sharon H Giordano; H Colleen Silva; Yong-Fang Kuo
Journal:  Cancer       Date:  2018-04-18       Impact factor: 6.860

9.  Malignancy Detection on Mammography Using Dual Deep Convolutional Neural Networks and Genetically Discovered False Color Input Enhancement.

Authors:  Philip Teare; Michael Fishman; Oshra Benzaquen; Eyal Toledano; Eldad Elnekave
Journal:  J Digit Imaging       Date:  2017-08       Impact factor: 4.056

10.  Evolution of breast cancer screening in the Medicare population: clinical and economic implications.

Authors:  Brigid K Killelea; Jessica B Long; Anees B Chagpar; Xiaomei Ma; Rong Wang; Joseph S Ross; Cary P Gross
Journal:  J Natl Cancer Inst       Date:  2014-07-16       Impact factor: 13.506

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