Skip to main content
SpringerLink
Log in

Cost-Effectiveness Models in Breast Cancer Screening in the General Population: A Systematic Review

  • Systematic Review
  • Published:
Applied Health Economics and Health Policy Aims and scope Submit manuscript

Abstract

Background

Many Western countries have long-established population-based mammography screening programs. Prior to implementing these programs, decision-analytic modeling was widely used to inform decisions.

Objective

The aim of this study was to perform a systematic review of cost-effectiveness models in breast cancer screening in the general population to analyze their structural and methodological approaches.

Methods

A systematic literature search for health economic models was performed in the electronic databases MEDLINE (Ovid), EMBASE, CRD Databases, Cochrane Library, and EconLit in August 2011 with updates in June 2013, April 2015, and November 2016. To assess studies systematically, a standardized form was applied to extract relevant information that was then summarized in evidence tables.

Results

Thirty-five studies were included; 27 state-transition models were analyzed using cohort (n = 12) and individual-level simulation (n = 15). Twenty-one studies modeled the natural history of breast cancer and predicted mortality as a function of the early detection modality. The models employed different assumptions regarding ductal carcinoma in situ. Thirteen studies performed cost-utility analyses with different sources for utility values, but assumptions were often made about utility weights. Twenty-two models did not report any validation.

Conclusion

State-transition modeling was the most frequently applied analytic approach. Different methods in modeling the progression of ductal carcinoma in situ to invasive cancer were identified because there is currently no agreement on the biological behavior of noninvasive breast cancer. Main weaknesses were the lack of precise utility estimates and insufficient reporting of validation. Sensitivity analyses of assumptions regarding ductal carcinoma in situ and in particular adequate validation are critical to minimize the risk of biased model outcomes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Torre LA, Bray F, Siegel RL, et al. Global cancer statistics, 2012. CA Cancer J Clin. 2015;65(2):87–108.

    Article  PubMed  Google Scholar 

  2. Luengo-Fernandez R, Leal J, Gray A, Sullivan R. Economic burden of cancer across the European Union: a population-based cost analysis. Lancet Oncol. 2013;14(12):1165–74.

    Article  PubMed  Google Scholar 

  3. American Cancer Society, Inc. The global economic cost of cancer. 2010. http://www.cancer.org/acs/groups/content/@internationalaffairs/documents/document/acspc-026203.pdf. Accessed 11 Nov 2016.

  4. Klabunde CN, Ballard-Barbash R. Evaluating population-based screening mammography programs internationally. Semin Breast Dis. 2007;10(2):102–7.

    Article  PubMed  PubMed Central  Google Scholar 

  5. World Health Organization. International Agency for Research on Cancer. IARC handbooks of cancer prevention. Vol. 7. In: Vainio H, Bianchini F, editors. Breast cancer screening. IARC Press; Lyon, 2002.

    Google Scholar 

  6. Humphrey LL, Helfand M, Chan BK, Woolf SH. Breast cancer screening: a summary of the evidence for the U.S. Preventive Services Task Force. Ann Intern Med. 2002;137(5 Part 1):347–60.

    Article  PubMed  Google Scholar 

  7. Butler JR, Furnival CM, Hart RF. The costs of treating breast cancer in Australia and the implications for breast cancer screening. Aust N Z J Surg. 1995;65(7):485–91.

    Article  CAS  PubMed  Google Scholar 

  8. Brown ML, Fintor L. Cost-effectiveness of breast cancer screening: preliminary results of a systematic review of the literature. Breast Cancer Res Treat. 1993;25(2):113–8.

    Article  CAS  PubMed  Google Scholar 

  9. Wolstenholme JL, Smith SJ, Whynes DK. The costs of treating breast cancer in the United Kingdom: implications for screening. Int J Technol Assess Health Care. 1998;14(2):277–89.

    Article  CAS  PubMed  Google Scholar 

  10. Cocquyt V, Moeremans K, Annemans L, et al. Long-term medical costs of postmenopausal breast cancer therapy. Ann Oncol. 2003;14(7):1057–63.

    Article  CAS  PubMed  Google Scholar 

  11. Elixhauser A. Costs of breast cancer and the cost-effectiveness of breast cancer screening. Int J Technol Health Care. 1991;7(4):604–15.

    Article  CAS  Google Scholar 

  12. Rashidian A, Barfar E, Hosseini H, et al. Cost effectiveness of breast cancer screening using mammography; a systematic review. Iran J Public Health. 2013;42(4):347–57.

    PubMed  PubMed Central  Google Scholar 

  13. Williams I, Bryan S. Understanding the limited impact of economic evaluation in health care resource allocation: a conceptual framework. Health Policy. 2007;80(1):135–43.

    Article  PubMed  Google Scholar 

  14. Williams I, Bryan S, McIver S. How should cost-effectiveness analysis be used in health technology coverage decisions? Evidence from the National Institute for Health and Clinical Excellence approach. J Health Serv Res Policy. 2007;12(2):73–9.

    Article  PubMed  Google Scholar 

  15. Sun X, Faunce T. Decision-analytical modelling in health-care economic evaluations. Eur J Health Econ. 2008;9(4):313–23.

    Article  PubMed  Google Scholar 

  16. Kulasingam SL, Havrilesky L, Ghebre R, Myers ER. U.S. Preventive Services Task Force evidence syntheses, formerly systematic evidence reviews. Screening for cervical cancer: a decision analysis for the US Preventive Services Task Force. Rockville (MD): US Agency for Healthcare Research and Quality; 2011.

  17. Zauber AG, Lansdorp-Vogelaar I, Knudsen AB, et al. Evaluating test strategies for colorectal cancer screening: a decision analysis for the U.S. Preventive Services Task Force. Ann Intern Med. 2008;149(9):659–69.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Holford NH, Kimko HC, Monteleone JP, Peck CC. Simulation of clinical trials. Ann Rev Pharmacol Toxicol. 2000;40:209–34.

    Article  CAS  Google Scholar 

  19. Siebert U. When should decision-analytic modeling be used in the economic evaluation of health care? Eur J Health Econ. 2003;4:143–50.

    Article  Google Scholar 

  20. Eddy DM. Clinical decision making: from theory to practice. Connecting value and costs: whom do we ask, and what do we ask them? JAMA. 1990;264(13):1737–9.

    Article  CAS  PubMed  Google Scholar 

  21. Mandelblatt J, Saha S, Teutsch S, et al. The cost-effectiveness of screening mammography beyond age 65 years: a systematic review for the U.S. Preventive Services Task Force. Ann Intern Med. 2003;139(10):835–42.

    Article  PubMed  Google Scholar 

  22. Koleva-Kolarova RG, Zhan Z, Greuter MJ, et al. Simulation models in population breast cancer screening: a systematic review. Breast. 2015;24(4):354–63.

    Article  PubMed  Google Scholar 

  23. Caro JJ, Briggs AH, Siebert U, Kuntz KM. Modeling good research practices: overview. a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-1. Med Decis Mak. 2012;32(5):667–77.

    Article  Google Scholar 

  24. Tufts Medical Center CEA Registry. http://healtheconomics.tuftsmedicalcenter.org/cear4/SearchingtheCEARegistry/SearchtheCEARegistry.aspx. Accessed 23 Nov 2016.

  25. Systematic reviews: CRD’s guidance for undertaking reviews in health care. York: University of York, Centre for Reviews and Dissemination; 2008. http://www.york.ac.uk/media/crd/Systematic_Reviews.pdf. Accessed 20 Jun 2016.

  26. Ward CE, Ashburner JM, He W, Atlas SJ. The association between patient experience of care and subsequent cancer prevention and chronic disease outcomes. J Gen Intern Med. 2013;28:S196–7.

    Google Scholar 

  27. Wever EM, Draisma G, Heijnsdijk EA, de Koning HJ. How does early detection by screening affect disease progression? Modeling estimated benefits in prostate cancer screening. Med Decis Mak. 2011;31(4):550–8.

    Article  Google Scholar 

  28. Surveillance, Epidemiology, and End Results Program, National Cancer Institute. https://seer.cancer.gov/tools/codingmanuals/historical.html. Accessed 24 Nov 2016.

  29. Briggs AH, Weinstein MC, Fenwick EA, et al. Model parameter estimation and uncertainty analysis: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force Working Group-6. Med Decis Mak. 2012;32(5):722–32.

    Article  Google Scholar 

  30. Eddy DM, Hollingworth W, Caro JJ, et al. Model transparency and validation: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-7. Med Decis Mak. 2012;32(5):733–43.

    Article  Google Scholar 

  31. Wong IO, Kuntz KM, Cowling BJ, et al. Cost-effectiveness analysis of mammography screening in Hong Kong Chinese using state-transition Markov modelling. Hong Kong Med J. 2010;16(Suppl. 3):38–41.

    PubMed  Google Scholar 

  32. van Oortmarssen GJ, Habbema JD, van der Maas PJ, et al. A model for breast cancer screening. Cancer. 1990;66(7):1601–12.

    Article  PubMed  Google Scholar 

  33. Stout NK, Rosenberg MA, Trentham-Dietz A, et al. Retrospective cost-effectiveness analysis of screening mammography. J Natl Cancer Inst. 2006;98(11):774–82.

    Article  PubMed  Google Scholar 

  34. Mittmann N, Stout NK, Lee P, et al. Total cost-effectiveness of mammography screening strategies. Health Rep. 2015;26(12):16–25.

    PubMed  PubMed Central  Google Scholar 

  35. Fryback DG, Stout NK, Rosenberg MA, et al. The Wisconsin Breast Cancer Epidemiology Simulation Model. J Natl Cancer Inst Monogr. 2006;36:37–47.

    Article  Google Scholar 

  36. Carles M, Vilaprinyo E, Cots F, Gregori A, Pla R, Roman R, et al. Cost-effectiveness of early detection of breast cancer in Catalonia (Spain). BMC Cancer. 2011;11:192.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Lee S, Zelen M. A stochastic model for predicting the mortality of breast cancer. J Natl Cancer Inst Monogr. 2006;36:79–86.

    Article  Google Scholar 

  38. Arveux P, Wait S, Schaffer P. Building a model to determine the cost-effectiveness of breast cancer screening in France. Eur J Cancer Care. 2003;12(2):143–53.

    Article  CAS  Google Scholar 

  39. Lejeune C, Arveux P, Dancourt V, et al. A simulation model for evaluating the medical and economic outcomes of screening strategies for colorectal cancer. Eur J Cancer Prev. 2003;12(1):77–84.

    Article  CAS  PubMed  Google Scholar 

  40. Lindfors KK, Rosenquist CJ, Lindfors KK, Rosenquist CJ. The cost-effectiveness of mammographic screening strategies [Erratum appears in JAMA. 1996 Jan 10;275(2):112]. JAMA. 1995;274(11):881–4.

    Article  CAS  PubMed  Google Scholar 

  41. Rosenquist CJ, Lindfors KK, Rosenquist CJ, Lindfors KK. Screening mammography in women aged 40–49 years: analysis of cost-effectiveness. Radiology. 1994;191(3):647–50.

    Article  CAS  PubMed  Google Scholar 

  42. Rosenquist CJ, Lindfors KK, Rosenquist CJ, Lindfors KK. Screening mammography beginning at age 40 years: a reappraisal of cost-effectiveness. Cancer. 1998;82(11):2235–40.

    Article  CAS  PubMed  Google Scholar 

  43. Lindfors KK, Rosenquist CJ. Needle core biopsy guided with mammography: a study of cost-effectiveness. Radiology. 1994;190(1):217–22.

    Article  CAS  PubMed  Google Scholar 

  44. Garuz R, Forcen T, Cabases J, et al. Economic evaluation of a mammography-based breast cancer screening programme in Spain. Eur J Public Health. 1997;7(1):68–76.

    Article  Google Scholar 

  45. Malcolm G. Cost-effectiveness of mammography screening options. N Z Econ Pap. 1993;27(2):161–83.

    Google Scholar 

  46. Knox EG, Knox EG. Evaluation of a proposed breast cancer screening regimen. BMJ. 1988;297(6649):650–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Okubo I, Glick H, Frumkin H, et al. Cost-effectiveness analysis of mass screening for breast cancer in Japan. Cancer. 1991;67(8):2021–9.

    Article  CAS  PubMed  Google Scholar 

  48. Pharoah PD, Sewell B, Fitzsimmons D, et al. Cost effectiveness of the NHS breast screening programme: life table model. BMJ. 2013;346:f2618.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Nystrom L, Rutqvist LE, Wall S, et al. Breast cancer screening with mammography: overview of Swedish randomised trials. Lancet. 1993;341(8851):973–8.

    Article  CAS  PubMed  Google Scholar 

  50. Andersson I, Aspegren K, Janzon L, et al. Mammographic screening and mortality from breast cancer: the Malmo mammographic screening trial. BMJ. 1988;297(6654):943–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Tabar L, Fagerberg G, Duffy SW, Day NE. The Swedish two county trial of mammographic screening for breast cancer: recent results and calculation of benefit. J Epidemiol Commun Health. 1989;43(2):107–14.

    Article  CAS  Google Scholar 

  52. Beemsterboer PM, de Koning HJ, Warmerdam PG, et al. Prediction of the effects and costs of breast-cancer screening in Germany. Int J Cancer. 1994;58(5):623–8.

    Article  CAS  PubMed  Google Scholar 

  53. Beemsterboer PMM, Warmerdam PG, Boer R, et al. Screening for breast cancer in Catalonia: which policy is to be preferred? Eur J Public Health. 1998;8(3):241–6.

    Article  Google Scholar 

  54. Boer R, de Koning HJ, van Oortmarssen GJ, van der Maas PJ. In search of the best upper age limit for breast cancer screening. Eur J Cancer. 1995;31A(12):2040–3.

    Article  CAS  PubMed  Google Scholar 

  55. Boer R, de Koning HJ, van der Maas PJ. A longer breast carcinoma screening interval for women age older than 65 years? Cancer. 1999;86(8):1506–10.

    Article  CAS  PubMed  Google Scholar 

  56. Boer R, de Koning H, Threlfall A, et al. Cost effectiveness of shortening screening interval or extending age range of NHS breast screening programme: computer simulation study. BMJ. 1998;317:376–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Carter R, Glasziou P, van Oortmarssen G, et al. Cost-effectiveness of mammographic screening in Australia. Aust J Public Health. 1993;17(1):42–50.

    Article  CAS  PubMed  Google Scholar 

  58. de Gelder R, Bulliard JL, de Wolf C, et al. Cost-effectiveness of opportunistic versus organised mammography screening in Switzerland. Eur J Cancer. 2009;45(1):127–38.

    Article  PubMed  Google Scholar 

  59. de Koning HJ, van Ineveld BM, van Oortmarssen GJ, 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(4):531–7.

    Article  PubMed  Google Scholar 

  60. Haghighat S, Akbari ME, Yavari P, et al. Cost-effectiveness of three rounds of mammography breast cancer screening in Iranian women. Iran J Cancer Prev. 2016;9(1):e5443.

    PubMed  PubMed Central  Google Scholar 

  61. BreastScreen Australia Evaluation. Economic evaluation and modelling study prepared by IMS Health Pty Ltd Australia for the Australian Government Department of Health and Ageing. 2009. http://webarchive.nla.gov.au/gov/20090929152622/http://www.cancerscreening.gov.au/internet/screening/publishing.nsf/Content/br-economic-cnt. Accessed 16 June 2016.

  62. Kerlikowske K, Salzmann P, Phillips KA, et al. Continuing screening mammography in women aged 70 to 79 years: impact on life expectancy and cost-effectiveness. JAMA. 1999;282(22):2156–63.

    Article  CAS  PubMed  Google Scholar 

  63. Madan J, Rawdin A, Stevenson M, Tappenden P. A rapid-response economic evaluation of the UK NHS Cancer Reform Strategy breast cancer screening program extension via a plausible bounds approach. Value Health. 2010;13(2):215–21.

    Article  PubMed  Google Scholar 

  64. Mandelblatt JS, Schechter CB, Yabroff KR, et al. Benefits and costs of interventions to improve breast cancer outcomes in African American women. J Clin Oncol. 2004;22(13):2554–66.

    Article  PubMed  Google Scholar 

  65. Neeser K, Szucs T, Bulliard JL, et al. Cost-effectiveness analysis of a quality-controlled mammography screening program from the Swiss statutory health-care perspective: quantitative assessment of the most influential factors. Value Health. 2007;10(1):42–53.

    Article  PubMed  Google Scholar 

  66. Pataky R, Phillips N, Peacock S, Coldman AJ. Cost-effectiveness of population-based mammography screening strategies by age range and frequency. J Cancer Policy. 2014;2(4):97–102.

    Article  Google Scholar 

  67. Rennert G, Rennert G. The value of mammography in different ethnic groups in Israel: analysis of mortality reduction and costs using CAN*TROL. Cancer Detect Prev. 1991;15(6):477–81.

    CAS  PubMed  Google Scholar 

  68. Rojnik K, Naversnik K, Mateovic-Rojnik T, Primiczakelj M. Probabilistic cost-effectiveness modeling of different breast cancer screening policies in Slovenia. Value Health. 2008;11(2):139–48.

    Article  PubMed  Google Scholar 

  69. Salzmann P, Kerlikowske K, Phillips K, et al. Cost-effectiveness of extending screening mammography guidelines to include women 40 to 49 years of age.[Erratum appears in Ann Intern Med 1998 May 15;128(10):878]. Ann Intern Med. 1997;127(11):955–65.

    Article  CAS  PubMed  Google Scholar 

  70. Sankatsing VD, Heijnsdijk EA, van Luijt PA, et al. Cost-effectiveness of digital mammography screening before the age of 50 in The Netherlands. Int J Cancer. 2015;137(8):1990–9.

    Article  CAS  PubMed  Google Scholar 

  71. Szeto KL, Devlin NJ, Szeto KL, Devlin NJ. The cost-effectiveness of mammography screening: evidence from a microsimulation model for New Zealand. Health Policy. 1996;38(2):101–15.

    Article  CAS  PubMed  Google Scholar 

  72. van der Maas PJ, de Koning HJ, van Ineveld BM, et al. The cost-effectiveness of breast cancer screening. Int J Cancer. 1989;43(6):1055–60.

    Article  PubMed  Google Scholar 

  73. van Ineveld BM, van Oortmarssen GJ, de Koning HJ, et al. How cost-effective is breast cancer screening in different EC countries? Eur J Cancer. 1993;29a(12):1663–8.

    Article  PubMed  Google Scholar 

  74. Wong IO, Kuntz KM, Cowling BJ, et al. Cost effectiveness of mammography screening for Chinese women. Cancer. 2007;110(4):885–95.

    Article  PubMed  Google Scholar 

  75. Yaffe MJ, Mittmann N, Lee P, et al. Modelling mammography screening for breast cancer in the Canadian context: modification and testing of a microsimulation model. Health Rep. 2015;26(12):3–8.

    PubMed  PubMed Central  Google Scholar 

  76. Vilaprinyo E, Gispert R, Martinez-Alonso M, et al. Competing risks to breast cancer mortality in Catalonia. BMC Cancer. 2008;8:331.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Rue M, Carles M, Vilaprinyo E, et al. Dissemination of periodic mammography and patterns of use, by birth cohort, in Catalonia (Spain). BMC Cancer. 2008;8:336.

    Article  PubMed  PubMed Central  Google Scholar 

  78. Vilaprinyo E, Rue M, Marcos-Gragera R, Martinez-Alonso M. Estimation of age- and stage-specific Catalan breast cancer survival functions using US and Catalan survival data. BMC Cancer. 2009;9:98.

    Article  PubMed  PubMed Central  Google Scholar 

  79. TNM Staging System: American Joint Committee on Cancer (AJCC). Available from https://cancerstaging.org/references-tools/Pages/What-is-Cancer-Staging.aspx. Accessed 11 Nov 2016.

  80. De Gelder R, Heijnsdijk EAM, Fracheboud J, et al. The effects of population-based mammography screening starting between age 40 and 50 in the presence of adjuvant systemic therapy. Int J Cancer. 2015;137(1):165–72.

    Article  PubMed  CAS  Google Scholar 

  81. Coldman AJ, Phillips N. False-positive screening mammograms and biopsies among women participating in a Canadian provincial breast screening program. Can J Public Health. 2012;103(6):e420–4.

    PubMed  Google Scholar 

  82. Coldman AJ, Phillips N. Breast cancer survival and prognosis by screening history. Br J Cancer. 2014;110(3):556–9.

    Article  CAS  PubMed  Google Scholar 

  83. Independent UK Panel on Breast Cancer Screening. The benefits and harms of breast cancer screening: an independent review. Lancet. 2012;380(9855):1778–86.

    Article  Google Scholar 

  84. de Haes JC, de Koning HJ, van Oortmarssen GJ, et al. The impact of a breast cancer screening programme on quality-adjusted life-years. Int J Cancer. 1991;49(4):538–44.

    Article  PubMed  Google Scholar 

  85. Hutton J, Brown R, Borowitz M, et al. A new decision model for cost-utility comparisons of chemotherapy in recurrent metastatic breast cancer. Pharmacoeconomics. 1996;9(Suppl. 2):8–22.

    Article  PubMed  Google Scholar 

  86. Hayman JA, Kabeto MU, Schipper MJ, et al. Assessing the benefit of radiation therapy after breast-conserving surgery for ductal carcinoma-in-situ. J Clin Oncol. 2005;23(22):5171–7.

    Article  PubMed  Google Scholar 

  87. Schleinitz MD, DePalo D, Blume J, Stein M. Can differences in breast cancer utilities explain disparities in breast cancer care? J Gen Intern Med. 2006;21(12):1253–60.

    Article  PubMed  PubMed Central  Google Scholar 

  88. Bonomi AE, Boudreau DM, Fishman PA, et al. Quality of life valuations of mammography screening. Qual Life Res. 2008;17(5):801–14.

    Article  PubMed  Google Scholar 

  89. Kind P, Hardman G, Macran S. UK population norms for EQ-5D: discussion paper series. York: University of York, Centre for Health Economics; 1999.

    Google Scholar 

  90. Peasgood T, Ward SE, Brazier J. Health-state utility values in breast cancer. J Expert Rev Pharmacoecon Outcomes Res. 2010;10(5):553–66.

    Article  Google Scholar 

  91. Liljegren G, Karlsson G, Bergh J, Holmberg L. The cost-effectiveness of routine postoperative radiotherapy after sector resection and axillary dissection for breast cancer stage I: results from a randomized trial. Ann Oncol. 1997;8(8):757–63.

    Article  CAS  PubMed  Google Scholar 

  92. Hall J, Gerard K, Salkeld G, Richardson J. A cost utility analysis of mammography screening in Australia. Soc Sci Med. 1992;34(9):993–1004.

    Article  CAS  PubMed  Google Scholar 

  93. Street AD, Posnett J, Threlfall AG, et al. Economic evaluation of proposed changes to the breast screening programme. Report P20/03. York: York Health Economics Consortium, University of York; 1996.

  94. Verbeek AL, Hendriks JH, Holland R, et al. Reduction of breast cancer mortality through mass screening with modern mammography: first results of the Nijmegen Project, 1975–1981. Lancet. 1984;1(8388):1222–4.

    Article  CAS  PubMed  Google Scholar 

  95. Collette HJ, Day NE, Rombach JJ, de Waard F. Evaluation of screening for breast cancer in a non-randomised study (the DOM project) by means of a case-control study. Lancet. 1984;1(8388):1224–6.

    Article  CAS  PubMed  Google Scholar 

  96. Tabar L, Fagerberg CJ, Gad A, et al. Reduction in mortality from breast cancer after mass screening with mammography: randomised trial from the Breast Cancer Screening Working Group of the Swedish National Board of Health and Welfare. Lancet. 1985;1(8433):829–32.

    Article  CAS  PubMed  Google Scholar 

  97. de Koning HJ, Boer R, Warmerdam PG, et al. Quantitative interpretation of age-specific mortality reductions from the Swedish breast cancer-screening trials. J Natl Cancer Inst. 1995;87(16):1217–23.

    Article  PubMed  Google Scholar 

  98. National Evaluation Team for Breast Cancer Screening. National evaluation of breast cancer screening in the Netherlands 1990–2011/2012. 13th evaluation report. Rotterdam: Erasmus MC University Medical Center Rotterdam, Radboud University Nijmegen Medical Centre; 2014.

  99. van Luijt PA, Fracheboud J, Heijnsdijk EA, et al. Nation-wide data on screening performance during the transition to digital mammography: observations in 6 million screens. Eur J Cancer. 2013;49(16):3517–25.

    Article  PubMed  Google Scholar 

  100. Moss SM, Cuckle H, Evans A, et al. Effect of mammographic screening from age 40 years on breast cancer mortality at 10 years’ follow-up: a randomised controlled trial. Lancet. 2006;368(9552):2053–60.

    Article  PubMed  Google Scholar 

  101. Roberts MM, Alexander FE, Anderson TJ, et al. Edinburgh trial of screening for breast cancer: mortality at seven years. Lancet. 1990;335(8684):241–6.

    Article  CAS  PubMed  Google Scholar 

  102. Alexander FE, Anderson TJ, Brown HK, et al. 14 years of follow-up from the Edinburgh randomised trial of breast-cancer screening. Lancet. 1999;353(9168):1903–8.

    Article  CAS  PubMed  Google Scholar 

  103. Shapiro S, Venet W, Strax P. Periodic screening for breast cancer: the Health Insurance Plan Project and its sequelae, 1963–1986. Baltimore: Johns Hopkins University Press; 1988.

    Google Scholar 

  104. Nystrom L, Andersson I, Bjurstam N, et al. Long-term effects of mammography screening: updated overview of the Swedish randomised trials. Lancet. 2002;359(9310):909–19.

    Article  PubMed  Google Scholar 

  105. Mandelblatt JS, Cronin KA, Bailey S, et al. Effects of mammography screening under different screening schedules: model estimates of potential benefits and harms. Ann Intern Med. 2009;151(10):738–47.

    Article  PubMed  PubMed Central  Google Scholar 

  106. Siebert U, Alagoz O, Bayoumi AM, et al. State-transition modeling: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-3. Med Decis Mak. 2012;32(5):690–700.

    Article  Google Scholar 

  107. Fone D, Hollinghurst S, Temple M, et al. Systematic review of the use and value of computer simulation modelling in population health and health care delivery. J Public Health Med. 2003;25(4):325–35.

    Article  PubMed  Google Scholar 

  108. Trikalinos TA, Siebert U, Lau J. AHRQ methods for effective health care, decision-analytic modeling to evaluate benefits and harms of medical tests: uses and limitations. Medical tests: White Paper series. Rockville: Agency for Healthcare Research and Quality; 2009.

  109. Shepard DS. Cost-effectiveness in health and medicine. In: Gold MR, Siegel JE, Russell LB, Weinstein MC, editors. New York: Oxford University Press; 1996. J Ment Health Policy Econ. 1999;2(2):91–2.

  110. Vemer P, Corro Ramos I, van Voorn GA, et al. AdViSHE: a validation-assessment tool of health-economic models for decision makers and model users. Pharmacoeconomics. 2016;34(4):349–61.

    Article  CAS  PubMed  Google Scholar 

  111. Cronin KA, Feuer EJ, Clarke LD, Plevritis SK. Impact of adjuvant therapy and mammography on U.S. mortality from 1975 to 2000: comparison of mortality results from the cisnet breast cancer base case analysis. J Natl Cancer Inst Monogr. 2006;36:112–21.

    Article  Google Scholar 

  112. Erbas B, Provenzano E, Armes J, Gertig D. The natural history of ductal carcinoma in situ of the breast: a review. Breast Cancer Res Treat. 2006;97(2):135–44.

    Article  PubMed  Google Scholar 

  113. Ernster VL, Ballard-Barbash R, Barlow WE, et al. Detection of ductal carcinoma in situ in women undergoing screening mammography. J Natl Cancer Inst. 2002;94(20):1546–54.

    Article  PubMed  Google Scholar 

  114. White E, Lee CY, Kristal AR. Evaluation of the increase in breast cancer incidence in relation to mammography use. J Nat Cancer Inst. 1990;82(19):1546–52.

    Article  CAS  PubMed  Google Scholar 

  115. Burstein HJ, Polyak K, Wong JS, et al. Ductal carcinoma in situ of the breast. N Engl J Med. 2004;350(14):1430–41.

    Article  CAS  PubMed  Google Scholar 

  116. de Gelder R, Heijnsdijk EA, van Ravesteyn NT, et al. Interpreting overdiagnosis estimates in population-based mammography screening. Epidemiol Rev. 2011;33:111–21.

    Article  PubMed  PubMed Central  Google Scholar 

  117. Virnig BA, Tuttle TM, Shamliyan T, Kane RL. Ductal carcinoma in situ of the breast: a systematic review of incidence, treatment, and outcomes. J Natl Cancer Inst. 2010;102(3):170–8.

    Article  PubMed  Google Scholar 

  118. Zelen M, Feinleib M. On the theory of screening of chronic diseases. Biometrika. 1969;56(3):601–14.

    Article  Google Scholar 

  119. Brennan VK, Wolowacz SE. A systematic review of breast cancer utility weights. In: Poster presentation at the International Society for Pharmacoeconomics and Outcomes Research 13th annual international meeting; Toronto, Canada, 2008.

  120. Brown DW, French MT, Schweitzer ME, et al. Economic evaluation of breast cancer screening: a review. Cancer Pract. 1999;7(1):28–33.

    Article  CAS  PubMed  Google Scholar 

  121. Kim SY, Goldie SJ. Cost-effectiveness analyses of vaccination programmes: a focused review of modelling approaches. Pharmacoeconomics. 2008;26(3):191–215.

    Article  PubMed  Google Scholar 

  122. Sassi F, Archard L, McDaid D. Searching literature databases for health care economic evaluations: how systematic can we afford to be? Med Care. 2002;40(5):387–94.

    Article  PubMed  Google Scholar 

  123. Hopewell S, McDonald S, Clarke M, Egger M. Grey literature in meta-analyses of randomized trials of health care interventions. Cochrane Database Syst Rev. 2007;2:MR000010.

    Google Scholar 

Download references

Acknowledgements

We thank Jen Manne-Goehler, MD, DSc, Clinical Fellow in Medicine, Harvard Medical School, for reviewing and editing the manuscript for English language. In addition, we would like to thank Tarquin Mittermayr, BA, Information Specialist at Ludwig Boltzmann Institute for Health Technology Assessment, who conducted the literature searches.

Author information

Authors and Affiliations

  1. Department of Evidence-Based Economic Health Care, Main Association of Austrian Social Security Institutions, Kundmanngasse 21, 1030, Vienna, Austria

    Irmgard C. Schiller-Frühwirth

  2. Department of Public Health, Health Services Research and Health Technology Assessment, University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria

    Irmgard C. Schiller-Frühwirth, Beate Jahn, Marjan Arvandi & Uwe Siebert

  3. Division of Health Technology Assessment and Bioinformatics, ONCOTYROL-Center for Personalized Cancer Medicine, Innsbruck, Austria

    Beate Jahn & Uwe Siebert

  4. Department of Radiology, Institute for Technology Assessment, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    Uwe Siebert

  5. Department of Health Policy and Management, Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Uwe Siebert

Authors
  1. Irmgard C. Schiller-Frühwirth
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Beate Jahn
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marjan Arvandi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Uwe Siebert
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Irmgard C. Schiller-Frühwirth.

Ethics declarations

Funding

This work was supported in part by the COMET Center ONCOTYROL, which is funded by the Austrian Federal Ministries BMVIT/BMWFJ (via FFG) and the Tiroler Zukunftsstiftung/Standortagentur Tirol (SAT). The funding source had no role in designing the study, interpreting the data, and writing or publishing the manuscript.

Conflict of interest

Irmgard Schiller-Frühwirth is an employee of the Main Association of Austrian Social Security Institutions and declares no conflicts of interest. Both authors, Beate Jahn and Uwe Siebert were employed by the sponsor. Marjan Arvandi is an employee of UMIT and declares no conflicts of interest.

Author contributions

IS-F conceptualized and performed the systematic review and wrote the report. BJ, MA, and US contributed to the study selection. IS-F, BJ, and MA screened for titles and abstracts but screened also the full papers. US determined the outcomes of any disagreements regarding study eligibility. IS-F extracted the data; BJ checked the completeness and accuracy of the extracted study information. The first author coordinated this work and made final decisions. BJ and US reviewed and recommended revisions to the final submitted manuscript.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOC 1.04 mb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Schiller-Frühwirth, I.C., Jahn, B., Arvandi, M. et al. Cost-Effectiveness Models in Breast Cancer Screening in the General Population: A Systematic Review. Appl Health Econ Health Policy 15, 333–351 (2017). https://doi.org/10.1007/s40258-017-0312-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40258-017-0312-3

Keywords

Search

Navigation