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DOES ONE SIZE FIT ALL? COST UTILITY ANALYSES OF ALTERNATIVE MAMMOGRAPHIC FOLLOW-UP SCHEDULES, BY RISK OF RECURRENCE

Published online by Cambridge University Press:  10 December 2015

Taryn Bessen Open the ORCID record for Taryn Bessen [Opens in a new window] ,
Dorothy M.K. Keefe  and
Jonathan Karnon
Taryn Bessen
Affiliation:
Department of Medical Imaging, Royal Adelaide HospitalTaryn.Bessen@health.sa.gov.au
Dorothy M.K. Keefe
Affiliation:
SA Cancer Service; Department of Cancer Medicine, University of Adelaide; Sansom Institute, University of South Australia; Royal Adelaide Hospital
Jonathan Karnon
Affiliation:
School of Population Health, University of Adelaide
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Abstract

Objectives: International guidelines recommend annual mammography after early breast cancer, but there is no randomized controlled trial evidence to support this schedule over any other. Given that not all women have the same risk of recurrence, it is possible that, by defining different risk profiles, we could tailor mammographic schedules that are more effective and efficient.

Methods: A discrete event simulation model was developed to describe the progression of early breast cancer after completion of primary treatment. Retrospective data for 1,100 postmenopausal women diagnosed with early breast cancer in South Australia from 2000 to 2008 were used to calibrate the model. Women were divided into four prognostic subgroups based on the Nottingham Prognostic Index of their primary tumor. For each subgroup, we compared the cost-effectiveness of three different mammographic schedules for two different age groups.

Results: Annual mammographic follow-up was not cost-effective for most postmenopausal women. Two yearly mammography was cost-effective for all women with excellent prognosis tumors; and for women with good prognosis tumors if high compliance rates can be achieved. Annual mammography for 5 years and 2 yearly surveillance thereafter (a mixed schedule) may be cost-effective for 50- to 69-year-old women with moderate prognosis tumors, and for women aged 70–79 years with poor prognosis tumors. For younger women with poor prognosis tumors, annual mammography is potentially cost-effective.

Conclusions: Our results suggest that mammographic follow-up could be tailored according to risk of recurrence. If validated with larger datasets, this could potentially set the stage for personalized mammographic follow-up after breast cancer.

Keywords

Early breast cancerMammographyFollow-upCost-effectiveness
Type
Assessments
Information
International Journal of Technology Assessment in Health Care , Volume 31 , Issue 5 , 2015 , pp. 281 - 288
Copyright
Copyright © Cambridge University Press 2015 

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Footnotes

The National Breast Cancer Foundation (NBCF) provided Doctoral Support (DS-10–02) for Taryn Bessen. Ron Somers, and Helen Thomas (South Australian Cancer Registry); Colin Rathael and Grant Emmerson (OACIS); Paul Basso and Deborah Brown (ISAAC); and Val Edyvean from Births, Deaths, and Marriages assisted with data access. Clarabelle Pham and Glenis Crane provided technical assistance; and Alicia Siggs, Elisia Rhue, Stefania de Stefano, Renee Bessen, Nikki Peters, and Danielle McCormick provided general research support. Source of funding: Taryn Bessen was the recipient of Doctoral Funding from the National Breast Cancer Foundation (NBCF) in Australia. The funding was to support project-related costs, and the NBCF had no input into the design, conduct, analysis, or reporting of this study. Author statement: We attest that (i) each author contributed to the conception and design or analysis and interpretation of data and the writing of the study; (ii) each has approved the version being submitted; and (iii) the content has not been published nor is being considered for publication elsewhere. Ethics approval: Ethics approval was obtained from the SA Health Human Research Ethics Committee to extract and link routinely collected data from the South Australian Cancer Registry, and clinical and administrative hospital databases (HREC Protocol number 352/03/2013). Financial support: Dr. Taryn Bessen was the recipient of Doctoral funding from the National Breast Cancer Foundation (NBCF) in Australia. The funding was to support project-related costs, and the NBCF had no input into the design, conduct, analysis, or reporting of this study.

References

REFERENCES

1. New Zealand Guidelines Group. Management of early breast cancer. Wellington: New Zealand: Guidelines Group; 2009.Google Scholar
2. National Institute for Health and Clinical Excellence. Early and locally advanced breast cancer: Diagnosis and treatment. Cardiff, Wales: National Collaborating Centre for Cancer; 2009.Google Scholar
3. National Breast and Ovarian Cancer Centre. Recommendations for follow-up of women with early breast cancer. Surry Hills, NSW: National Breast and Ovarian Cancer Centre; 2010.Google Scholar
4. Khatcheressian, J, Hurley, P, Bantug, E, et al. Breast cancer follow-up and management after primary treatment: American Society of Clinical Oncology clinical practice guideline update. J Clin Oncol. 2013;31:961–965.Google Scholar
5. Aebi, S, Davidson, T, Gruber, G, et al. Primary breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2011;22 (Suppl 6):vi12–24.Google Scholar
6. Scottish Intercollegiate Guidelines Network. Management of breast cancer in women. A national clinical guideline. Edinburgh, Scotland: Scottish Intercollegiate Guidelines Network; 2005.Google Scholar
7. Grunfeld, E, Dhesy-Thind, S, Levine, M, et al. Clinical practice guidelines for the care and treatment of breast cancer: Follow-up after treatment for breast cancer (summary of the 2005 update). CMAJ. 2005;172:1319–1320.Google Scholar
8. Grunfeld, E, Noorani, H, McGahan, L, et al. Surveillance mammography after treatment of primary breast cancer: A systematic review. Breast. 2002;11:228–235.Google Scholar
9. Robertson, C, Arcot Ragupathy, S, Boachie, C, et al. The clinical effectiveness and cost-effectiveness of different surveillance mammography regimens after the treatment for primary breast cancer: Systematic reviews registry database analyses and economic evaluation. Health Technol Assess. 2011;15:1–322.Google Scholar
10. Bessen, T, Karnon, J. A patient-level calibration framework for evaluating surveillance strategies: A case study of mammographic follow-up after early breast cancer. Value Health. 2014;17:669–678.Google Scholar
11. Galea, M, Blamey, R, Elston, C, et al. The Nottingham Prognostic Index in primary breast cancer. Breast Cancer Res Treat. 1992;22:207–219.Google Scholar
12. Australian Institute of Health and Welfare & Australasian Association of Cancer Registries 2012. Cancer in Australia: An overview, 2012 (Cancer series no.74, Cat.no. CAN 70). Canberra, Australia: Australian Institute of Health and Welfare; 2012.Google Scholar
13. Verry, H, Lord, S, Martin, A, et al. Effectiveness and cost-effectiveness of sentinel lymph node biopsy compared with axillary node dissection in patients with early-stage breast cancer: A decision model analysis. Br J Cancer. 2012;106:1045–1052.Google Scholar
14. Peasgood, T, Ward, S, Brazier, J. Health-state utility values in breast cancer. Expert Rev Pharmacoecon Outcomes Res. 2010;10:553–566.Google Scholar
15. Tengs, T, Wallace, A. One thousand health-related quality-of-life estimates. Med Care. 2000;38:583–637.Google Scholar
16. de Koning, H, van Ineveld, B, van Oortmarssen, G, et al. Breast cancer screening and cost-effectiveness: Policy alternatives, quality of life considerations and the possible impact of uncertain factors. Int J Cancer. 1991;49:531–537.Google Scholar
17. Australian Institute of Health and Welfare (AIHW) 2012. ACIM (Australian Cancer Incidence and Mortality) Books. AIHW: Canberra. Breast cancer (ICD10 C50), Australia, 1968–2007. Age specific mortality rates. http://www.aihw.gov.au/WorkArea/DownloadAsset.aspx?id = 60129542435 (accessed August 6, 2013).Google Scholar
18. Australian Bureau of Statistics. 3302.0.55.001 - Life Tables, Australia, 2003–2005. http://abs.gov.au/AUSSTATS/abs@.nsf/allprimarymainfeatures/6A75A50AE791F95FCA25738D000F462B (accessed August 6, 2013).Google Scholar
19. Vanni, T, Karnon, J, Madan, J, et al. Calibrating models in economic evaluation: A seven step approach. Pharmacoeconomics. 2011;29:35–49.Google Scholar
20. Karnon, J, Goyder, E, Tappenden, P, et al. A review and critique of modelling in prioritising and designing screening programmes. Health Technol Assess. 2007;11:1–145.Google Scholar
21. Blamey, R, Ellis, I, Pinder, S, et al. Survival of invasive breast cancer according to the Nottingham Prognostic Index in cases diagnosed in 1990–1999. Eur J Cancer. 2007;43:1548–1555.Google Scholar
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