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Estimating prevalence of distant metastatic breast cancer: a means of filling a data gap

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Abstract

Purpose

To develop and validate a method for estimating numbers of people with distant cancer metastases, for evidence-based service planning.

Methods

Estimates were made employing an illness-death model with distant metastatic cancer as the illness state- and site-specific mortality as an outcome, using MIAMOD software. To demonstrate the method, we estimated numbers of females alive in Australia following detection of distant metastatic breast cancer during 1980–2004, using data on patient survival from an Australian population-based cancer registry. We validated these estimates by comparing them with direct prevalence counts.

Results

Relative survival at 10 years following detection of distant metastases was low (5–20 %), with better survival experienced by: (1) females where distant metastatic disease was detected at initial diagnosis rather than subsequently (e.g., at recurrence); (2) those diagnosed in more recent calendar years; and (3) younger age groups. For Australian females aged less than 85 years, the modeled cumulative risk of detection of distant metastatic breast cancer (either at initial diagnosis or subsequently) declined over time, but numbers of cases with this history rose from 71 per 100,000 in 1980 to 84 per 100,000 in 2004. The model indicated that there were approximately 3–4 prevalent distant metastatic breast cancer cases for every breast cancer death. Comparison of estimates with direct prevalence counts showed a reasonable level of agreement.

Conclusions

The method is straightforward to apply and we recommend its use for breast and other cancers when registry data are insufficient for direct prevalence counts. This will provide estimates of numbers of people who would need ongoing medical surveillance and care following detection of distant metastases.

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Abbreviations

NSW:

New South Wales

MIAMOD:

Mortality and incidence analysis model

HR:

Hazard ratio

CI:

Confidence interval

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Acknowledgments

This work was supported by the National Breast and Ovarian Cancer Centre and by the Australian National Health and Medical Research Council, through a Career Development Award (Ref 471491) to Mark Clements and a Training Fellowship (Ref 550002) to Xue Qin Yu. We thank the New South Wales Central Cancer Registry for providing the data, members of a National Breast and Ovarian Cancer Centre advisory committee for their guidance, and an anonymous referee for comments that considerably improved the article. This research was instigated by consumers, particularly by the late Sue Lockwood.

Conflict of interest

Professor Roder was an employee of the National Breast and Ovarian Cancer Centre.

Author information

Authors and Affiliations

  1. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

    Mark S. Clements

  2. National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australia

    Mark S. Clements

  3. National Breast and Ovarian Cancer Centre, Sydney, Australia

    David M. Roder

  4. Cancer Council NSW, Sydney, Australia

    Xue Qin Yu, Sam Egger & Dianne L. O’Connell

  5. University of Sydney, Sydney, Australia

    Dianne L. O’Connell

  6. University of New South Wales, Sydney, Australia

    Dianne L. O’Connell

  7. University of Newcastle, Newcastle, Australia

    Dianne L. O’Connell

Authors
  1. Mark S. Clements
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  2. David M. Roder
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  3. Xue Qin Yu
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  4. Sam Egger
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  5. Dianne L. O’Connell
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Corresponding author

Correspondence to Mark S. Clements.

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Clements, M.S., Roder, D.M., Yu, X.Q. et al. Estimating prevalence of distant metastatic breast cancer: a means of filling a data gap. Cancer Causes Control 23, 1625–1634 (2012). https://doi.org/10.1007/s10552-012-0040-9

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  • DOI: https://doi.org/10.1007/s10552-012-0040-9

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