Patient-centered simulations to assess the usefulness of the 70-gene signature for adjuvant chemotherapy administration in early-stage breast cancer

  • Emmanuel Caruana
  • Yohann Foucher
  • Philippe Tessier
  • Jean-Sébastien Frenel
  • Jean-Marc Classe
  • Etienne DantanEmail author



From the MINDACT trial, Cardoso et al. did not demonstrate a significant efficacy for adjuvant chemotherapy (CT) for women with early-stage breast cancer presenting high clinical and low genomic risks. Our objective was to assess the usefulness of the 70-gene signature in this population by using an alternative endpoint: the number of Quality-Adjusted Life-Years (QALYs), i.e., a synthetic measure of quantity and quality of life.


Based on the results of the MINDACT trial, we simulated a randomized clinical trial consisting of 1497 women with early-stage breast cancer presenting high clinical and low genomic risks. The individual preferences for the different health states and corresponding decrements were obtained from the literature.


The gain in terms of 5-year disease-free survival was 2.8% (95% CI from − 0.1 to 5.7%, from 90.4% for women without CT to 93.3% for women with CT). In contrast, due to the associated side effects, CT significantly reduced the number of QALYs by 62 days (95% CI from 55 to 70 days, from 4.13 years for women without CT to 3.96 years for women with CT).


Our results support the conclusions published by Cardoso et al. by providing additional evidence that the 70-gene signature can be used to avoid overtreatment by CT for women with high clinical risk but low genomic risk.


70-gene signature Breast cancer Patient-centered outcomes Stratified medicine Adjuvant chemotherapy 


95% CI

95% confidence interval


Adjuvant breast cancer trial


Cyclophosphamide, methotrexate, and fluorouracil




Disease-free survival


Distant metastasis-free survival


Early-stage breast cancer


Epirubicin followed by cyclophosphamide, methotrexate, fluorouracil


European organisation for research and treatment of cancer


Fluorouracil, epirubicin, and cyclophosphamide


FEC60 followed by docetaxel


Health-related quality of life


Hazard ratio


Microarray in node-negative disease may avoid chemotherapy


National epirubicin adjuvant trial


Quality-adjusted life-years


Taxotere as adjuvant chemotherapy trial



This work was supported by the Cancer National Institute (INCa, MAP-MARKER, No. 2013-137).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Research involving human participants and/or animals

This article does not contain any studies with animals performed by any of the authors.

Informed consent

For this type of study formal consent is not required.

Supplementary material

10549_2018_5107_MOESM1_ESM.docx (56 kb)
Supplementary material 1 (DOCX 55 KB)


  1. 1.
    Ravdin PM, Siminoff LA, Davis GJ et al (2001) Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol 19:980–991. CrossRefGoogle Scholar
  2. 2.
    Buyse M, Loi S, van’t Veer L et al (2006) Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer. J Natl Cancer Inst 98:1183–1192. CrossRefGoogle Scholar
  3. 3.
    Bueno-de-Mesquita JM, Linn SC, Keijzer R et al (2009) Validation of 70-gene prognosis signature in node-negative breast cancer. Breast Cancer Res Treat 117:483–495. CrossRefGoogle Scholar
  4. 4.
    Mook S, Schmidt MK, Viale G et al (2009) The 70-gene prognosis-signature predicts disease outcome in breast cancer patients with 1–3 positive lymph nodes in an independent validation study. Breast Cancer Res Treat 116:295–302. CrossRefGoogle Scholar
  5. 5.
    van’t Veer LJ, Dai H, van de Vijver MJ et al (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415:530–536. CrossRefGoogle Scholar
  6. 6.
    Harris L, Fritsche H, Mennel R et al (2007) American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer. J Clin Oncol 25:5287–5312. CrossRefGoogle Scholar
  7. 7.
    Cardoso F, van’t Veer LJ, Bogaerts J et al (2016) 70-Gene signature as an aid to treatment decisions in early-stage breast cancer. N Engl J Med 375:717–729. CrossRefGoogle Scholar
  8. 8.
    Lange S, Scheibler F, Fleer D, Windeler J (2017) Interpretation of the results of the MINDACT Study and consequent recommendations in the updated ASCO clinical practice guideline. JCO 36:429–430. CrossRefGoogle Scholar
  9. 9.
    Harris LN, Ismaila N, McShane LM et al (2016) Use of biomarkers to guide decisions on adjuvant systemic therapy for women with early-stage invasive breast cancer: American Society of Clinical Oncology Clinical Practice Guideline. J Clin Oncol 34:1134–1150. CrossRefGoogle Scholar
  10. 10.
    Krop I, Ismaila N, Andre F et al (2017) Use of biomarkers to guide decisions on adjuvant systemic therapy for women with early-stage invasive breast cancer: American Society of Clinical Oncology Clinical Practice Guideline Focused Update. J Clin Oncol 35:2838–2847. CrossRefGoogle Scholar
  11. 11.
    Thewes B, Prins J, Friedlander M (2016) 70-gene signature in early-stage breast cancer. N Engl J Med 375:2199–2200. CrossRefGoogle Scholar
  12. 12.
    Basch E (2013) Toward patient-centered drug development in oncology. N Engl J Med 369:397–400. CrossRefGoogle Scholar
  13. 13.
    Foucher Y, Lorent M, Tessier P et al (2018) A mini-review of quality of life as an outcome in prostate cancer trials: patient-centered approaches are needed to propose appropriate treatments on behalf of patients. Health Qual Life Outcomes 16:40. CrossRefGoogle Scholar
  14. 14.
    Sloan JA, Sargent DJ, Novotny PJ et al (2014) Calibration of quality-adjusted life years for oncology clinical trials. J Pain Symptom Manag 47:1091–1099.e3. CrossRefGoogle Scholar
  15. 15.
    Dantan E, Foucher Y, Lorent M et al (2016) Optimal threshold estimator of a prognostic marker by maximizing a time-dependent expected utility function for a patient-centered stratified medicine. Stat Methods Med Res 096228021667116.
  16. 16.
    Health related quality of life by age, gender and history of cardiovascular disease: results from the Health Survey for England—HEDS_DP_09_12.pdf. Accessed 20 Nov 2017
  17. 17.
    Campbell HE, Epstein D, Bloomfield D et al (2011) The cost-effectiveness of adjuvant chemotherapy for early breast cancer: A comparison of no chemotherapy and first, second, and third generation regimens for patients with differing prognoses. Eur J Cancer 47:2517–2530. CrossRefGoogle Scholar
  18. 18.
    Dolan P, Gudex C, Kind P, Williams A (1995) A social tariff for EuroQol: results from a UK general population survey. Centre for Health Economics, University of YorkGoogle Scholar
  19. 19.
    Weinstein MC, Torrance G, McGuire A (2009) QALYs: the basics. Value Health 12(Suppl 1):S5–S9. CrossRefGoogle Scholar
  20. 20.
    Poisot T (2011) The digitize package: extracting numerical data from scatterplots. R J 3:25–26Google Scholar
  21. 21.
    R Development Core Team (2010) R: a language and environment for statistical computing. Vienna, AustriaGoogle Scholar
  22. 22.
    Flores M, Glusman G, Brogaard K et al (2013) P4 medicine: how systems medicine will transform the healthcare sector and society. Per Med 10:565–576. CrossRefGoogle Scholar
  23. 23.
    Duffy MJ, Harbeck N, Nap M et al (2017) Clinical use of biomarkers in breast cancer: Updated guidelines from the European Group on Tumor Markers (EGTM). Eur J Cancer 75:284–298. CrossRefGoogle Scholar
  24. 24.
    Sparano JA, Gray RJ, Makower DF et al (2018) Adjuvant chemotherapy guided by a 21-gene expression assay in breast cancer. N Engl J Med 379:111–121. CrossRefGoogle Scholar
  25. 25.
    Collinson FJ, Gregory WM, McCabe C et al (2012) The STAR trial protocol: a randomised multi-stage phase II/III study of Sunitinib comparing temporary cessation with allowing continuation, at the time of maximal radiological response, in the first-line treatment of locally advanced/metastatic Renal Cancer. BMC Cancer. Google Scholar
  26. 26.
    Royce TJ, Feldman AS, Mossanen M et al (2018) Comparative effectiveness of bladder-preserving tri-modality therapy versus radical cystectomy for muscle-invasive bladder cancer. Clin Genitourin Cancer. Google Scholar
  27. 27.
    Ferguson ND, Scales DC, Pinto R et al (2013) Integrating Mortality and Morbidity Outcomes. Am J Respir Crit Care Med 187:256–261. CrossRefGoogle Scholar
  28. 28.
    Glasziou PP, Simes RJ, Gelber RD (1990) Quality adjusted survival analysis. Stat Med 9:1259–1276. CrossRefGoogle Scholar
  29. 29.
    Cole BF, Gelber RD, Goldhirsch A (1993) Cox regression models for quality adjusted survival analysis. Stat Med 12:975–987CrossRefGoogle Scholar
  30. 30.
    Aaronson NK, Ahmedzai S, Bergman B et al (1993) The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst 85:365–376. CrossRefGoogle Scholar
  31. 31.
    Towse A (2010) Net clinical benefit: the art and science of jointly estimating benefits and risks of medical treatment. Value Health 13(Suppl 1):S30–S32. CrossRefGoogle Scholar
  32. 32.
    Kind P, Lafata JE, Matuszewski K, Raisch D (2009) The use of QALYs in clinical and patient decision-making: issues and prospects. Value Health 12(Suppl 1):S27–S30. CrossRefGoogle Scholar
  33. 33.
    Ellis P, Barrett-Lee P, Johnson L et al (2009) Sequential docetaxel as adjuvant chemotherapy for early breast cancer (TACT): an open-label, phase III, randomised controlled trial. Lancet 373:1681–1692. CrossRefGoogle Scholar
  34. 34.
    Poole CJ, Earl HM, Hiller L et al (2006) Epirubicin and Cyclophosphamide, methotrexate, and fluorouracil as adjuvant therapy for early breast cancer. N Engl J Med 355:1851–1862. CrossRefGoogle Scholar
  35. 35.
    Adjuvant Breast Cancer Trials Collaborative Group (2007) Polychemotherapy for early breast cancer: results from the international adjuvant breast cancer chemotherapy randomized trial. J Natl Cancer Inst 99:506–515. CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.INSERM UMR 1246 -SPHERE, Nantes University, Tours UniversityNantesFrance
  2. 2.Nantes University HospitalNantesFrance
  3. 3.Institut de Cancérologie de l’Ouest, Centre René GauducheauSaint-HerblainFrance

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