Breast Cancer Research and Treatment

, Volume 129, Issue 2, pp 401–409 | Cite as

Economic issues involved in integrating genomic testing into clinical care: the case of genomic testing to guide decision-making about chemotherapy for breast cancer patients

  • Patricia MarinoEmail author
  • Carole Siani
  • François Bertucci
  • Henri Roche
  • Anne-Laure Martin
  • Patrice Viens
  • Valérie Seror
Preclinical study


The use of taxanes to treat node-positive (N+) breast cancer patients is associated with heterogeneous benefits as well as with morbidity and financial costs. This study aimed to assess the economic impact of using gene expression profiling to guide decision-making about chemotherapy, and to discuss the coverage/reimbursement issues involved. Retrospective data on 246 patients included in a randomised trial (PACS01) were analyzed. Tumours were genotyped using DNA microarrays (189-gene signature), and patients were classified depending on whether or not they were likely to benefit from chemotherapy regimens without taxanes. Standard anthracyclines plus taxane chemotherapy (strategy AT) was compared with the innovative strategy based on genomic testing (GEN). Statistical analyses involved bootstrap methods and sensitivity analyses. The AT and GEN strategies yielded similar 5-year metastasis-free survival rates. In comparison with AT, GEN was cost-effective when genomic testing costs were less than 2,090€. With genomic testing costs higher than 2,919€, AT was cost-effective. Considering a 30% decrease in the price of docetaxel (the patent rights being about to expire), GEN was cost-effective if the cost of genomic testing was in the 0€–1,139€ range; whereas AT was cost-effective if genomic testing costs were higher than 1,891€. The use of gene expression profiling to guide decision-making about chemotherapy for N+ breast cancer patients is potentially cost-effective. Since genomic testing and the drugs targeted in these tests yield greater well-being than the sum of those resulting from separate use, questions arise about how to deal with extra well-being in decision-making about coverage/reimbursement.


Cost-effectiveness Breast cancer Genomic testing Adjuvant chemotherapy 



This study was supported by a grant from the “Fondation de France”. The authors thank Dr. Jessica Blanc for revising the English manuscript. The authors also thank Christian de Peretti for valuable discussions about bootstrap.


  1. 1.
    Davis JC, Furstenthal L, Desai AA, Norris T, Sutaria S, Fleming E, Ma P (2009) The microeconomics of personalized medicine: today’s challenge and tomorrow’s promise. Nat Rev Drug Discov 8(4):279–286PubMedCrossRefGoogle Scholar
  2. 2.
    Phillips KA, Veenstra DL, Ramsey SD, Van Bebber SL, Sakowski J (2004) Genetic testing and pharmacogenomics: issues for determining the impact to healthcare delivery and costs. Am J Manag Care 10(7):425–432PubMedGoogle Scholar
  3. 3.
    Houtsma D, Guchelaar HJ, Gelderblom H (2010) Pharmacogenetics in oncology: a promising field. Curr Pharm Des 16(2):155–163PubMedCrossRefGoogle Scholar
  4. 4.
    Vegter S, Boersma C, Rozenbaum M, Wilffert B, Navis G, Postma MJ (2008) Pharmacoeconomic evaluations of pharmacogenetic and genomic screening programmes: a systematic review on content and adherence to guidelines. Pharmacoeconomics 26(7):569–587PubMedCrossRefGoogle Scholar
  5. 5.
    Deverka PA (2009) Pharmacogenomics, evidence, and the role of payers. Public Health Genomics 12(3):149–157PubMedCrossRefGoogle Scholar
  6. 6.
    Drummond M, O’Brien B, Stoddart G (1997) Methods for the economic evaluation of health care programs, 2nd edn. Oxford Medical Publications, Oxford University Press, New YorkGoogle Scholar
  7. 7.
    Evans BJ (2007) Distinguishing product and practice regulation in personalized medicine. Clin Pharmacol Ther 81(2):288–293PubMedCrossRefGoogle Scholar
  8. 8.
    van’t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, Peterse HL, van der Kooy K, Marton MJ, Witteveen AT et al (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415(6871):530–536CrossRefGoogle Scholar
  9. 9.
    van de Vijver MJ, He YD, van’t Veer LJ, Dai H, Hart AA, Voskuil DW, Schreiber GJ, Peterse JL, Roberts C, Marton MJ et al (2002) A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 347(25):1999–2009PubMedCrossRefGoogle Scholar
  10. 10.
    Bertucci F, Finetti P, Cervera N, Maraninchi D, Viens P, Birnbaum D (2006) Gene expression profiling and clinical outcome in breast cancer. Omics 10(4):429–443PubMedCrossRefGoogle Scholar
  11. 11.
    Bray F, Sankila R, Ferlay J, Parkin DM (2002) Estimates of cancer incidence and mortality in Europe in 1995. Eur J Cancer 38(1):99–166PubMedCrossRefGoogle Scholar
  12. 12.
    Early Breast Cancer Trialists’ Cooperative Group (2005) Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet 365(9472):1687–1717CrossRefGoogle Scholar
  13. 13.
    Piccart MJ, de Valeriola D, Dal Lago L, de Azambuja E, Demonty G, Lebrun F, Bernard-Marty C, Colozza M, Cufer T (2005) Adjuvant chemotherapy in 2005: standards and beyond. Breast 14(6):439–445PubMedCrossRefGoogle Scholar
  14. 14.
    Mamounas EP, Bryant J, Lembersky B, Fehrenbacher L, Sedlacek SM, Fisher B, Wickerham DL, Yothers G, Soran A, Wolmark N (2005) Paclitaxel after doxorubicin plus cyclophosphamide as adjuvant chemotherapy for node-positive breast cancer: results from NSABP B-28. J Clin Oncol 23(16):3686–3696PubMedCrossRefGoogle Scholar
  15. 15.
    Martin M, Pienkowski T, Mackey J, Pawlicki M, Guastalla JP, Weaver C, Tomiak E, Al-Tweigeri T, Chap L, Juhos E et al (2005) Adjuvant docetaxel for node-positive breast cancer. N Engl J Med 352(22):2302–2313PubMedCrossRefGoogle Scholar
  16. 16.
    Roche H, Fumoleau P, Spielmann M, Canon JL, Delozier T, Serin D, Symann M, Kerbrat P, Soulie P, Eichler F et al (2006) Sequential adjuvant epirubicin-based and docetaxel chemotherapy for node-positive breast cancer patients: the FNCLCC PACS 01 Trial. J Clin Oncol 24(36):5664–5671PubMedCrossRefGoogle Scholar
  17. 17.
    Buzdar AU, Singletary SE, Valero V, Booser DJ, Ibrahim NK, Rahman Z, Theriault RL, Walters R, Rivera E, Smith TL et al (2002) Evaluation of paclitaxel in adjuvant chemotherapy for patients with operable breast cancer: preliminary data of a prospective randomized trial. Clin Cancer Res 8(5):1073–1079PubMedGoogle Scholar
  18. 18.
    Bria E, Nistico C, Cuppone F, Carlini P, Ciccarese M, Milella M, Natoli G, Terzoli E, Cognetti F, Giannarelli D (2006) Benefit of taxanes as adjuvant chemotherapy for early breast cancer: pooled analysis of 15,500 patients. Cancer 106(11):2337–2344PubMedCrossRefGoogle Scholar
  19. 19.
    Campone M, Fumoleau P, Bourbouloux E, Kerbrat P, Roche H (2005) Taxanes in adjuvant breast cancer setting: which standard in Europe? Crit Rev Oncol Hematol 55(3):167–175PubMedCrossRefGoogle Scholar
  20. 20.
    Veenstra DL, Higashi MK, Phillips KA (2000) Assessing the cost-effectiveness of pharmacogenomics. AAPS PharmSci 2(3):E29PubMedCrossRefGoogle Scholar
  21. 21.
    Flowers CR, Veenstra D (2004) The role of cost-effectiveness analysis in the era of pharmacogenomics. Pharmacoeconomics 22(8):481–493PubMedCrossRefGoogle Scholar
  22. 22.
    Guttmacher AE, Collins FS (2002) Genomic medicine—a primer. N Engl J Med 347(19):1512–1520PubMedCrossRefGoogle Scholar
  23. 23.
    Bertucci F, Nasser V, Granjeaud S, Eisinger F, Adelaide J, Tagett R, Loriod B, Giaconia A, Benziane A, Devilard E et al (2002) Gene expression profiles of poor-prognosis primary breast cancer correlate with survival. Hum Mol Genet 11(8):863–872PubMedCrossRefGoogle Scholar
  24. 24.
    Bertucci F, Borie N, Roche H, Bachelot T, Le Doussal JM, Macgrogan G, Debono S, Martinec A et al (2010) Gene expression profile predicts outcome after anthracycline-based adjuvant chemotherapy in early breast cancer. Breast Cancer Res Treat. doi: 10.1007/s10549-010-1003-z
  25. 25.
    Marino P, Siani C, Roché H, Protière C, Fumoleau P, Spielmann M, Martin A-L, Viens P, Le Corroller Soriano A-G (2010) Cost-effectiveness of adjuvant docetaxel for node-positive breast cancer patients: results of the PACS 01 economic study. Ann Oncol 21(7):1448–1454Google Scholar
  26. 26.
    Finkler SA (1982) The distinction between cost and charges. Ann Intern Med 96(1):102–109PubMedGoogle Scholar
  27. 27.
    Sims AH, Ong KR, Clarke RB, Howell A (2006) High-throughput genomic technology in research and clinical management of breast cancer. Exploiting the potential of gene expression profiling: is it ready for the clinic? Breast Cancer Res 8(5):214PubMedCrossRefGoogle Scholar
  28. 28.
    Roden DM, Altman RB, Benowitz NL, Flockhart DA, Giacomini KM, Johnson JA, Krauss RM, McLeod HL, Ratain MJ, Relling MV et al (2006) Pharmacogenomics: challenges and opportunities. Ann Intern Med 145(10):749–757PubMedGoogle Scholar
  29. 29.
    Swen JJ, Huizinga TW, Gelderblom H, de Vries EG, Assendelft WJ, Kirchheiner J, Guchelaar HJ (2007) Translating pharmacogenomics: challenges on the road to the clinic. PLoS Med 4(8):e209PubMedCrossRefGoogle Scholar
  30. 30.
    Ross JS, Hatzis C, Symmans WF, Pusztai L, Hortobagyi GN (2008) Commercialized multigene predictors of clinical outcome for breast cancer. Oncologist 13(5):477–493PubMedCrossRefGoogle Scholar
  31. 31.
    Lyman GH, Kuderer NM (2006) Gene expression profile assays as predictors of recurrence-free survival in early-stage breast cancer: a metaanalysis. Clin Breast Cancer 7(5):372–379PubMedCrossRefGoogle Scholar
  32. 32.
    Hornberger J, Cosler LE, Lyman GH (2005) Economic analysis of targeting chemotherapy using a 21-gene RT-PCR assay in lymph-node-negative, estrogen-receptor-positive, early-stage breast cancer. Am J Manag Care 11(5):313–324PubMedGoogle Scholar
  33. 33.
    Lyman GH, Cosler LE, Kuderer NM, Hornberger J (2007) Impact of a 21-gene RT-PCR assay on treatment decisions in early-stage breast cancer: an economic analysis based on prognostic and predictive validation studies. Cancer 109(6):1011–1018PubMedCrossRefGoogle Scholar
  34. 34.
    Oestreicher N, Ramsey SD, Linden HM, McCune JS, van’t Veer LJ, Burke W, Veenstra DL (2005) Gene expression profiling and breast cancer care: what are the potential benefits and policy implications? Genet Med 7(6):380–389PubMedCrossRefGoogle Scholar
  35. 35.
    Chen MK, Nalebuff B (2006) One-way essential complements. Cowles Foundation Discussion Paper, vol 1588, Yale UniversityGoogle Scholar
  36. 36.
    Gabszewicz J, Sonnac N, Wauthy X (2001) On price competition with complementary goods. Econ Lett 70(3):431–437CrossRefGoogle Scholar
  37. 37.
    Hirth RA, Chernew ME, Miller E, Fendrick AM, Weissert WG (2000) Willingness to pay for a quality-adjusted life year: in search of a standard. Med Decis Making 20(3):332–342PubMedCrossRefGoogle Scholar
  38. 38.
    Pinto-Prades JL, Loomes G, Brey R (2009) Trying to estimate a monetary value for the QALY. J Health Econ 28(3):553–562PubMedCrossRefGoogle Scholar
  39. 39.
    Mason H, Jones-Lee M, Donaldson C (2009) Modelling the monetary value of a QALY: a new approach based on UK data. Health Econ 18(8):933–950PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC. 2010

Authors and Affiliations

  • Patricia Marino
    • 1
    • 2
    • 3
    Email author
  • Carole Siani
    • 4
  • François Bertucci
    • 2
    • 3
    • 5
    • 6
  • Henri Roche
    • 7
  • Anne-Laure Martin
    • 8
  • Patrice Viens
    • 2
    • 3
    • 6
    • 9
  • Valérie Seror
    • 1
    • 2
  1. 1.Inserm, UMR 912 “Economic & Social Sciences, Health Systems & Societies”, IRDMarseillesFrance
  2. 2.Université Aix-MarseilleMarseillesFrance
  3. 3.Institut Paoli-CalmettesMarseillesFrance
  4. 4.ERIC EA 3083University of Lyon (University Claude Bernard Lyon 1)LyonFrance
  5. 5.Centre de Recherche en Cancérologie de Marseille, Département d’Oncologie MoléculaireInserm, UMR 891MarseilleFrance
  6. 6.IFR137MarseilleFrance
  7. 7.Institut Claudius RégaudToulouseFrance
  8. 8.Fédération Nationale des Centres de Lutte Contre le CancerParisFrance
  9. 9.Centre de Recherche en Cancérologie de Marseille, Département d’oncologie médicaleInserm, UMR 891MarseilleFrance

Personalised recommendations