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Estimating Individual Cancer Risks in the UK National Breast Screening Programme: A Feasibility Study

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Digital Mammography (IWDM 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5116))

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Abstract

Conventional risk models for the development of breast cancer use inputs such as age, weight, hormonal factors and family history to compute individual breast cancer risk. These are employed in the management of women at high risk. The addition of breast density as an input has been shown to improve the accuracy of such models. An improved risk model could facilitate risk-based population screening. However, in order to use breast density in risk models there is a need to employ objective methods for measuring the density. A feasibility study has been carried out to assess the practicality of using a stepwedge-based technique for measuring breast density from mammograms in the UK National Health Service Breast Screening Programme and to determine whether additional information, relevant to risk, can be collected by questionnaire. Preliminary results suggest that it is practical to use such a technique in the screening environment. In a sample of 100 women, the mean density was 27% (range 2 - 81%). A negative trend in breast density was observed with Body Mass Index.

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References

  1. Gail, M.H., Brinton, L.A., Byar, D.P., Corle, D.K., Green, S.B., Schairer, C., Mulvhill, J.J.: Projecting individualised probabilities of developing breast cancer for white females who are being examined annually. J. Nat. Can. Inst. 81(24), 1879–1886 (1989)

    Article  Google Scholar 

  2. Claus, E.B., Risch, N., Thompson, W.D.: Autosomal dominant inheritance of early-onset breast cancer: implications for risk prediction. Cancer 73(3), 643–651 (1994)

    Article  Google Scholar 

  3. Ford, D., Easton, D.F.: The genetics of breast and ovaraian cancer. Br. J. Cancer. 72(4), 805–812 (1995)

    Google Scholar 

  4. Ford, D., Easton., D.F., Stratton, M., Narod, S., Goldgar, D., Devilee, P., Bishop, D.T., Weber, B., Lenoir, G., Chang-Claude, S.J., Teare, H., Struewing, M.D., Arason, J., Scherneck, A., Peto, S., Rebbeck, J., Tonin, T.R., Neuhausen, P., Barkardottir, S.R., Eyfjord, J., Lynch, H., Ponder, B.A., Gayther, S.A., Zelada-Hedman, M.: The Breast Cancer Linkage Consortium: Genetic heterogeneity and penetrance analysis of the BRCA1 and BRCA2 genes in breast cancer families. Am. J. Hum. Genet. 62, 676–689 (1998)

    Article  Google Scholar 

  5. Amir, E., Evans, D.G., Shenton, A., Lalloo, F., Boggis, C., Wilson, M., Howell, A.: Evaluation of breast cancer risk assessment packages in the family history evaluation and screening programme. J. Med. Genet. 40, 807–814 (2003)

    Article  Google Scholar 

  6. Tyrer, J., Duffy, S.W., Cuzick, J.: A breast cancer prediction model incorporating familial and personal risk factors. Statisitics in Medicine 23, 1111–1130 (2004)

    Article  Google Scholar 

  7. Barlow, W.E., White, E., Ballard-Barbash, R., Vacek, P.M., Titus-Ernstoff, L., Carney, P.A., Tice, J.A., Buist, D.S.M., Geller, B.M., Rosenberg, R., Yankaskas, B.C., Kerlikowske, K.: Prospective breast cancer risk prediction model for women undergoing screening mammography. J. Nat. Can. Inst. 98(17), 1204–1212 (2006)

    Article  Google Scholar 

  8. American College of Radiology. Illustrated Breast Imaging Reporting and Data System (BI-RADS TM ), 4th edn. Reston (VA): ACR (2003)

    Google Scholar 

  9. UK Office of National Statistics: Obesity among adults: by sex and NS-SeC (2001), http://www.statistics.gov.uk/StatBase/ssdataset.asp?vlnk=7447&More=Y

  10. Berks, M., Diffey, J., Hufton, A., Astley, S.: Feasibility and Acceptability of Stepwedge-Based Density Measurement. In: Astley, S.M., Brady, M., Rose, C., Zwiggelaar, R. (eds.) IWDM 2006. LNCS, vol. 4046, pp. 355–361. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  11. Patel, H.G., Astley, S.M., Hufton, A.P., Harvie, M., Hagan, K., Marchant, T.E., Hillier, V., Howell, A.: Automated breast tissue measurement of women at increased risk of breast cancer. In: Astley, S.M., Brady, M., Rose, C., Zwiggelaar, R. (eds.) IWDM 2006. LNCS, vol. 4046, pp. 131–136. Springer, Heidelberg (2006)

    Google Scholar 

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Elizabeth A. Krupinski

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© 2008 Springer-Verlag Berlin Heidelberg

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Diffey, J., Hufton, A., Astley, S., Mercer, C., Maxwell, A. (2008). Estimating Individual Cancer Risks in the UK National Breast Screening Programme: A Feasibility Study. In: Krupinski, E.A. (eds) Digital Mammography. IWDM 2008. Lecture Notes in Computer Science, vol 5116. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70538-3_65

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  • DOI: https://doi.org/10.1007/978-3-540-70538-3_65

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-70537-6

  • Online ISBN: 978-3-540-70538-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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