Literature DB >> 16005226

Cancer detection and mammogram volume of radiologists in a population-based screening programme.

Mary Rickard1, Richard Taylor, Andrew Page, Jane Estoesta.   

Abstract

This study investigates the relationship between the number of screening mammograms read by radiologists and the screening breast cancer detection rate. Cancer detection rates for incident screens (all women aged 40 years) were compared by increasing categories of reader volume using Poisson regression. Data from New South Wales (NSW) for a 2 year period (2000-2001) were obtained from the BreastScreen NSW programme. Cancer detection rates increased with the number of mammograms read in the programme, reaching a plateau of approximately 40 per 10,000 after 1375 mammograms per year. No significant differences in cancer detection were evident above 875 mammograms (compared to below 875 mammograms) per year (RR=0.79, 95% CI 0.63-0.99).

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Mesh:

Year:  2005        PMID: 16005226     DOI: 10.1016/j.breast.2005.04.005

Source DB:  PubMed          Journal:  Breast        ISSN: 0960-9776            Impact factor:   4.380


  4 in total

1.  Disparities in screening mammography services by race/ethnicity and health insurance.

Authors:  Garth H Rauscher; Kristi L Allgood; Steve Whitman; Emily Conant
Journal:  J Womens Health (Larchmt)       Date:  2011-09-23       Impact factor: 2.681

2.  Radiologist characteristics associated with interpretive performance of diagnostic mammography.

Authors:  Diana L Miglioretti; Rebecca Smith-Bindman; Linn Abraham; R James Brenner; Patricia A Carney; Erin J Aiello Bowles; Diana S M Buist; Joann G Elmore
Journal:  J Natl Cancer Inst       Date:  2007-12-11       Impact factor: 13.506

Review 3.  Statistical approaches for modeling radiologists' interpretive performance.

Authors:  Diana L Miglioretti; Sebastien J P A Haneuse; Melissa L Anderson
Journal:  Acad Radiol       Date:  2009-02       Impact factor: 3.173

4.  Interpretive Performance and Inter-Observer Agreement on Digital Mammography Test Sets.

Authors:  Sung Hun Kim; Eun Hye Lee; Jae Kwan Jun; You Me Kim; Yun Woo Chang; Jin Hwa Lee; Hye Won Kim; Eun Jung Choi
Journal:  Korean J Radiol       Date:  2019-02       Impact factor: 3.500

  4 in total

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