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Predictive factors of pathologic complete response of HER2-positive breast cancer after preoperative chemotherapy with trastuzumab: development of a specific predictor and study of its utilities using decision curve analysis

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Abstract

Purpose

The aim of this study was to assess the Institut Gustave Roussy/M.D. Anderson Cancer Center (IGR/MDACC) nomogram in predicting pathologic complete response (pCR) to preoperative chemotherapy in a cohort of human epidermal growth factor receptor 2 (HER2)-positive tumors treated with preoperative chemotherapy with trastuzumab. We then combine clinical and pathological variables associated with pCR into a new nomogram specific to HER2-positive tumors treated by preoperative chemotherapy with trastuzumab.

Patients and methods

Data from 270 patients with HER2-positive tumors treated with preoperative chemotherapy with trastuzumab at the Institut Curie and at the Georges François Leclerc Cancer Center were used to assess the IGR/MDACC nomogram and to subsequently develop a new nomogram for pCR based on multivariate logistic regression. Model performance was quantified in terms of calibration and discrimination. We studied the utility of the new nomogram using decision curve analysis.

Results

The IGR/MDACC nomogram was not accurate for the prediction of pCR in HER2-positive tumors treated by preoperative chemotherapy with trastuzumab, with poor discrimination (AUC = 0.54, 95% CI 0.51–0.58) and poor calibration (p = 0.01). After uni- and multivariate analysis, a new pCR nomogram was built based on T stage (TNM), hormone receptor status, and Ki67 (%). The model had good discrimination with an area under the curve (AUC) at 0.74 (95% CI 0.70–0.79) and adequate calibration (p = 0.93). By decision curve analysis, the model was shown to be relevant between thresholds of 0.3 and 0.7.

Conclusion

To the best of our knowledge, ours is the first nomogram to predict pCR in HER2-positive tumors treated by preoperative chemotherapy with trastuzumab. To ensure generalizability, this model needs to be externally validated.

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References

  1. van der Hage JA, van de Velde CJ, Julien JP et al (2001) Preoperative chemotherapy in primary operable breast cancer: results from the European Organization for Research and Treatment of Cancer trial 10902. J Clin Oncol 19:4224–4237

    PubMed  Google Scholar 

  2. Schwartz GF, Hortobagyi GN (2004) Proceedings of the consensus conference on neoadjuvant chemotherapy in carcinoma of the breast, April 26–28, 2003, Philadelphia, Pennsylvania. Cancer 100:2512–2532. doi:10.1002/cncr.20298

    Article  PubMed  Google Scholar 

  3. Sachelarie I, Grossbard ML, Chadha M et al (2006) Primary systemic therapy of breast cancer. Oncologist 11:574–589. doi:10.1634/theoncologist.11-6-574

    Article  CAS  PubMed  Google Scholar 

  4. Gown AM, Goldstein LC, Barry TS et al (2008) High concordance between immunohistochemistry and fluorescence in situ hybridization testing for HER2 status in breast cancer requires a normalized IHC scoring system. Mod Pathol 21:1271–1277. doi:10.1038/modpathol.2008.83

    Article  CAS  PubMed  Google Scholar 

  5. Rastogi P, Anderson SJ, Bear HD et al (2008) Preoperative chemotherapy: updates of national surgical adjuvant breast and bowel project protocols B-18 and B-27. J Clin Oncol 26:778–785. doi:10.1200/JCO.2007.15.0235

    Article  PubMed  Google Scholar 

  6. Guarneri V, Broglio K, Kau S-W et al (2006) Prognostic value of pathologic complete response after primary chemotherapy in relation to hormone receptor status and other factors. J Clin Oncol 24:1037–1044. doi:10.1200/JCO.2005.02.6914

    Article  PubMed  Google Scholar 

  7. von Minckwitz G, Untch M, Blohmer J-U et al (2012) Definition and impact of pathologic complete response on prognosis after neoadjuvant chemotherapy in various intrinsic breast cancer subtypes. J Clin Oncol 30:1796–1804. doi:10.1200/JCO.2011.38.8595

    Article  Google Scholar 

  8. Cortazar P, Zhang L, Untch M et al (2014) Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet Lond Engl 384:164–172. doi:10.1016/S0140-6736(13)62422-8

    Article  Google Scholar 

  9. Rouzier R, Pusztai L, Delaloge S et al (2005) Nomograms to predict pathologic complete response and metastasis-free survival after preoperative chemotherapy for breast cancer. J Clin Oncol 23:8331–8339. doi:10.1200/JCO.2005.01.2898

    Article  PubMed  Google Scholar 

  10. Buzdar AU, Ibrahim NK, Francis D et al (2005) Significantly higher pathologic complete remission rate after neoadjuvant therapy with trastuzumab, paclitaxel, and epirubicin chemotherapy: results of a randomized trial in human epidermal growth factor receptor 2-positive operable breast cancer. J Clin Oncol 23:3676–3685. doi:10.1200/JCO.2005.07.032

    Article  CAS  PubMed  Google Scholar 

  11. Gianni L, Eiermann W, Semiglazov V et al (2010) Neoadjuvant chemotherapy with trastuzumab followed by adjuvant trastuzumab versus neoadjuvant chemotherapy alone, in patients with HER2-positive locally advanced breast cancer (the NOAH trial): a randomised controlled superiority trial with a parallel HER2-negative cohort. Lancet 375:377–384. doi:10.1016/S0140-6736(09)61964-4

    Article  CAS  PubMed  Google Scholar 

  12. Frati A, Chereau E, Coutant C et al (2012) Comparison of two nomograms to predict pathologic complete responses to neoadjuvant chemotherapy for breast cancer: evidence that HER2-positive tumors need specific predictors. Breast Cancer Res Treat 132:601–607. doi:10.1007/s10549-011-1897-0

    Article  CAS  PubMed  Google Scholar 

  13. Sataloff DM, Mason BA, Prestipino AJ et al (1995) Pathologic response to induction chemotherapy in locally advanced carcinoma of the breast: a determinant of outcome. J Am Coll Surg 180:297–306

    CAS  PubMed  Google Scholar 

  14. Chevallier B, Roche H, Olivier JP et al (1993) Inflammatory breast cancer. Pilot study of intensive induction chemotherapy (FEC-HD) results in a high histologic response rate. Am J Clin Oncol 16:223–228

    Article  CAS  PubMed  Google Scholar 

  15. R Core Team (2014). R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/. Frank E Harrell Jr., with contributions from Charles Dupont and many others. (2014). Hmisc: Harrell Miscellaneous

  16. Whitcher B (2012) Waveslim: basic wavelet routines for one-, two- and three-dimensional signal processing. R package version 1.7.1. The Comprehensive R Archive Network (CRAN). http://cran.r-project.org/package=waveslim

  17. R package version 1.7.5. http://cran.rproject.org/package=waveslim

  18. Frank E Harrell Jr (2014). Rms: regression modeling strategies. R package version 4.2-1

  19. Coutant C, Olivier C, Lambaudie E et al (2009) Comparison of models to predict nonsentinel lymph node status in breast cancer patients with metastatic sentinel lymph nodes: a prospective multicenter study. J Clin Oncol 27:2800–2808. doi:10.1200/JCO.2008.19.7418

    Article  PubMed  Google Scholar 

  20. Cox DR (1958) Two further applications of a model for binary regression. Biometrika 45:562–565

    Article  Google Scholar 

  21. Vickers AJ, Elkin EB (2006) Decision curve analysis: a novel method for evaluating prediction models. Med Decis Mak 26:565–574. doi:10.1177/0272989X06295361

    Article  Google Scholar 

  22. Kaufmann M, von Minckwitz G, Bear HD et al (2007) Recommendations from an international expert panel on the use of neoadjuvant (primary) systemic treatment of operable breast cancer: new perspectives 2006. Ann Oncol 18:1927–1934. doi:10.1093/annonc/mdm201

    Article  CAS  PubMed  Google Scholar 

  23. Kuerer HM, Newman LA, Smith TL et al (1999) Clinical course of breast cancer patients with complete pathologic primary tumor and axillary lymph node response to doxorubicin-based neoadjuvant chemotherapy. J Clin Oncol 17:460–469

    CAS  PubMed  Google Scholar 

  24. Rouzier R, Extra J-M, Klijanienko J et al (2002) Incidence and prognostic significance of complete axillary downstaging after primary chemotherapy in breast cancer patients with T1 to T3 tumors and cytologically proven axillary metastatic lymph nodes. J Clin Oncol 20:1304–1310

    Article  PubMed  Google Scholar 

  25. Fisher B, Bryant J, Wolmark N et al (1998) Effect of preoperative chemotherapy on the outcome of women with operable breast cancer. J Clin Oncol 16:2672–2685

    CAS  PubMed  Google Scholar 

  26. von Minckwitz G, Untch M, Nüesch E et al (2011) Impact of treatment characteristics on response of different breast cancer phenotypes: pooled analysis of the German neo-adjuvant chemotherapy trials. Breast Cancer Res Treat 125:145–156. doi:10.1007/s10549-010-1228-x

    Article  Google Scholar 

  27. Untch M, Rezai M, Loibl S et al (2010) Neoadjuvant treatment with trastuzumab in HER2-positive breast cancer: results from the GeparQuattro study. J Clin Oncol 28:2024–2031. doi:10.1200/JCO.2009.23.8451

    Article  CAS  PubMed  Google Scholar 

  28. Coudert BP, Arnould L, Moreau L et al (2006) Pre-operative systemic (neo-adjuvant) therapy with trastuzumab and docetaxel for HER2-overexpressing stage II or III breast cancer: results of a multicenter phase II trial. Ann Oncol 17:409–414. doi:10.1093/annonc/mdj096

    Article  CAS  PubMed  Google Scholar 

  29. Guiu S, Gauthier M, Coudert B et al (2010) Pathological complete response and survival according to the level of HER-2 amplification after trastuzumab-based neoadjuvant therapy for breast cancer. Breast J Cancer 103:1335–1342. doi:10.1038/sj.bjc.6605939

    CAS  Google Scholar 

  30. R. Rouzier, C. Bonneau, C. Huchon, C. Coutant (2014) Pathologies mammaires et cancer du sein: modèles statistiques. In: Mises À Jour En Gynécologie Médicale. Diffusion Vigot-Paris, pp 423–434

  31. Graesslin O, Abdulkarim BS, Coutant C et al (2010) Nomogram to predict subsequent brain metastasis in patients with metastatic breast cancer. J Clin Oncol 28:2032–2037. doi:10.1200/JCO.2009.24.6314

    Article  PubMed  Google Scholar 

  32. Jia Z, Lilly MB, Koziol JA et al (2014) Generation of “virtual” control groups for single arm prostate cancer adjuvant trials. PLoS ONE. doi:10.1371/journal.pone.0085010

    Google Scholar 

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Authors and Affiliations

  1. Department of Surgical Oncology, Georges-François Leclerc Cancer Center, Dijon, France

    Clémentine Jankowski, M. Cortet & C. Coutant

  2. University of Burgundy, Dijon, France

    Clémentine Jankowski & C. Coutant

  3. Department of Medical Oncology, Institut du cancer, Montpellier, France

    S. Guiu

  4. Department on Pathology, Georges-François Leclerc Cancer Center, Dijon, France

    C. Charon-Barra, L. Arnould, P. Fumoleau & B. Coudert

  5. Department of Medical Oncology, Georges-François Leclerc Cancer Center, Dijon, France

    Clémentine Jankowski, I. Desmoulins & V. Lorgis

  6. Department of Surgical Oncology, Curie Institute, Paris, France

    R. Rouzier & F. Reyal

Authors
  1. Clémentine Jankowski
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  2. S. Guiu
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  3. M. Cortet
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Correspondence to Clémentine Jankowski.

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C. Coutant is a Co-senior author.

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Jankowski, C., Guiu, S., Cortet, M. et al. Predictive factors of pathologic complete response of HER2-positive breast cancer after preoperative chemotherapy with trastuzumab: development of a specific predictor and study of its utilities using decision curve analysis. Breast Cancer Res Treat 161, 73–81 (2017). https://doi.org/10.1007/s10549-016-4040-4

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