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GENE EXPRESSION PROFILING AND EXPANDED IMMUNOHISTOCHEMISTRY TESTS TO GUIDE SELECTION OF CHEMOTHERAPY REGIMENS IN BREAST CANCER MANAGEMENT: A SYSTEMATIC REVIEW

Published online by Cambridge University Press:  10 May 2017

Alison Scope ,
Munira Essat ,
Abdullah Pandor ,
Rachid Rafia ,
Sue E. Ward ,
Lynda Wyld ,
Simon Cross  and
Helen Buckley Woods
Alison Scope
Affiliation:
School of Health and Related Research (ScHARR), The University of Sheffielda.scope@sheffield.ac.uk
Munira Essat
Affiliation:
School of Health and Related Research (ScHARR), The University of Sheffield
Abdullah Pandor
Affiliation:
School of Health and Related Research (ScHARR), The University of Sheffield
Rachid Rafia
Affiliation:
School of Health and Related Research (ScHARR), The University of Sheffield
Sue E. Ward
Affiliation:
School of Health and Related Research (ScHARR), The University of Sheffield
Lynda Wyld
Affiliation:
Royal Hallamshire Hospital, Sheffield
Simon Cross
Affiliation:
Royal Hallamshire Hospital, Sheffield
Helen Buckley Woods
Affiliation:
School of Health and Related Research (ScHARR), The University of Sheffield
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Abstract

Objectives: The aim of this report was to assess the clinical effectiveness of two Gene expression profiling (GEP) and two expanded immunohistochemistry (IHC) tests compared with current prognostic tools in guiding the use of adjuvant chemotherapy in patients with early breast cancer.

Methods: A systematic review of the evidence on clinical effectiveness of OncotypeDX, IHC4, MammaPrint, and Mammostrat, compared with current clinical practice using clinicopathological parameters, in women with early breast cancer was conducted. Ten databases were searched to include citations to May 2016.

Results: Searches identified 7,064 citations, of which forty-one citations satisfied the criteria for the review. A narrative synthesis was performed. Evidence for OncotypeDX demonstrated the impact of the test on decision making and there was some support for OncotypeDX predicting chemotherapy benefit. There were relatively lower levels of evidence for the other three tests included in the analysis. MammaPrint, Mammostrat, and IHC4 tests were limited to a small number of studies. Limitations in relation to study design were identified for all tests.

Conclusions: The evidence base for OncotypeDX is considered to be the most robust. Methodological weaknesses relating to heterogeneity of patient cohorts and issues arising from the retrospective nature of the evidence were identified. Further evidence is required for all of the tests using prospective randomized controlled trial data.

Keywords

Gene expression profilingImmunohistochemistryBreast cancer
Type
Assessments
Information
International Journal of Technology Assessment in Health Care , Volume 33 , Issue 1 , 2017 , pp. 32 - 45
Copyright
Copyright © Cambridge University Press 2017 

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References

REFERENCES

1. Perou, CM, Sørlie, T, Eisen, MB, et al. Molecular portraits of human breast tumours. Nature. 2000;406:747–752.Google Scholar
2. Senkus, E, Kyriakides, S, Ohno, S, et al. on behalf of the ESMO Guidelines Committee. Primary breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2015;26 (Suppl 5):v8-v30.Google Scholar
3. Ward, S, Scope, A, Rafia, R, et al. Gene expression profiling and expanded immunohistochemistry tests to guide the use of adjuvant chemotherapy in breast cancer management: A systematic review and cost-effectiveness analysis. Health Technol Assess. 2013;17:1–302.Google Scholar
4. Centre for Reviews and Dissemination. Systematic reviews: CRD's guidance for undertaking reviews in healthcare. York, UK: Centre for Reviews and Dissemination; 2009.Google Scholar
5. Liberati, A, Altman, D, Tetslaff, J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: Explanation and elaboration. BMJ. 2009;339:b2700.Google Scholar
6. National Institute for Health and Care Excellence. NICE Diagnostic Assessment Programme interim methods statement (pilot). London: NICE; 2010.Google Scholar
7. Marchionni, L, Wilson, R, Marinopoulos, S, et al. Impact of gene expression profiling tests on breast cancer outcomes. Evidence Report/Technology Assessment No. 160. Rockville, MD: Agency for Healthcare Research and Quality; 2008.Google Scholar
8. Smartt, P. A comparison of gene expression profiling tests for breast cancer. HSAC Report. 2010; 3 (16). Christchurch, New Zealand: Health Services Assessment Collaboration.Google Scholar
9. Altman, D. Systematic reviews in health care: Systematic reviews of evaluations of prognostic variables. BMJ. 2001;323:224–228.Google Scholar
10. Paik, S, Tang, G, Shak, S, et al. Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol. 2006;24:3726–3734.Google Scholar
11. Albain, KS, Barlow, WE, Shak, S, et al. Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal women with nodepositive, oestrogen-receptor-positive breast cancer on chemotherapy: A retrospective analysis of a randomised trial. Lancet Oncol. 2010;11:55–65.Google Scholar
12. Tang, G, Shak, S, Paik, S, et al. Comparison of the prognostic and predictive utilities of the 21-gene recurrence score assay and Adjuvant! for women with node-negative, ER-positive breast cancer: Results from NSABP B-14 and NSABP B-20. Breast Cancer Res Treat. 2011;127:133–142.Google Scholar
13. Tang, G, Constantino, J, Crager, M, Shak, S, Wolmark, N. [S4-9] Comparing the prediction of chemotherapy benefit in patients with node-negative, ER-positive breast cancer using the recurrence score and a new measure that integrates clinical and pathologic factors with the recurrence score. Proceedings of the 33rd Annual San Antonio Breast Cancer Symposium, 8-12 December, 2010.Google Scholar
14. Ross, D, Kim, C-Y, Tang, G, et al. Chemosensitivity and stratification by a five monoclonal antibody immunohistochemistry test in the NASBP B14 and B20 trials. Clin Cancer Res. 2008;14:6602–6609.Google Scholar
15. Oratz, R, Paul, D, Cohn, A, Sedlacek, S. Impact of a commercial reference laboratory test recurrence score on decision making in early-stage breast cancer. J Oncol Pract. 2007;3:182–186.Google Scholar
16. Asad, J, Jacobson, A, Estabrook, A, et al. Does Oncotype DX recurrence score affect the management of patients with early-stage breast cancer? Am J Surg. 2008;196:527–529.Google Scholar
17. Rayhanabad, J, Difronzo, L, Haigh, P, Romero, L. Changing paradigms in breast cancer management: Introducing molecular genetics into the treatment algorithm. Am J Surg. 2008;74:887–890.Google Scholar
18. Geffen, DB, Amir, N, Sion-Vardy, N, et al. Stage I breast cancer in a regional oncology practice in Israel 2002-2006: Clinicopathologic features, risk estimation and planned therapy of 328 consecutive patients. Breast. 2009;18:316–321.Google Scholar
19. Henry, L, Stojadinovic, A, Swain, S, et al. The influence of a gene expression profile on breast cancer decisions. J Surg Oncol. 2009;99: 319–323.Google Scholar
20. Klang, SH, Hammerman, A, Liebermann, N, et al. Economic implications of 21-gene breast cancer risk assay from the perspective of an Israeli-managed health-care organization. Value Health. 2010;13:381–387.Google Scholar
21. Lo, SS, Mumby, PB, Norton, J, et al. Prospective multicenter study of the impact of the 21-gene recurrence score assay on medical oncologist and patient adjuvant breast cancer treatment selection. J Clin Oncol. 2010;28:1671–1676.Google Scholar
22. Ademuyiwa, FO, Miller, A, O'Connor, T, et al. The effects of oncotype DX recurrence scores on chemotherapy utilization in a multi-institutional breast cancer cohort. Breast Cancer Res Treat. 2011;126:797–802.Google Scholar
23. Geffen, DB, Abu-Ghanem, S, Sion-Vardy, N, et al. The impact of the 21-gene recurrence score assay on decision making about adjuvant chemotherapy in early-stage estrogen-receptor-positive breast cancer in an oncology practice with a unified treatment policy. Ann Oncol. 2011; 22:2381–2386.Google Scholar
24. Joh, JE, Esposito, NN, Kiluk, JV, et al. The effect of Oncotype DX recurrence score on treatment recommendations for patients with estrogen receptor-positive early stage breast cancer and correlation with estimation of recurrence risk by breast cancer specialists. Oncologist. 2011;16:1520–1526.Google Scholar
25. Partin, JF, Mamounas, EP. Impact of the 21-gene recurrence score assay compared with standard clinicopathologic guidelines in adjuvant therapy selection for node-negative, estrogen receptor-positive breast cancer. Ann Surg Oncol. 2011;18:3399–3406.Google Scholar
26. Albanell, J, Gonzalez, A, Ruiz-Borrego, M, et al. Prospective transGEICAM study of the impact of the 21-gene Recurrence Score assay and traditional clinicopathological factors on adjuvant clinical decision making in women with estrogen receptor positive (ER?) node-negative breast cancer. Ann Oncol. 2012;23:625–631.Google Scholar
27. Bargallo, JE, Lara, F, Shaw-Dulin, R, et al. A study of the impact of the 21-gene breast cancer assay on the use of adjuvant chemotherapy in women with breast cancer in a Mexican public hospital. J Surg Oncol. 2015;111:203–207.Google Scholar
28. Biroschak, JR, Schwartz, GF, Palazzo, JP, et al. Impact of Oncotype DX on treatment decisions in ER-positive, node-negative breast cancer with histologic correlation. Breast J. 2013;19:269–275.Google Scholar
29. Davidson, JA, Cromwell, I, Ellard, SL, et al. A prospective clinical utility and pharmacoeconomic study of the impact of the 21-gene Recurrence Score assay in oestrogen receptor positive node negative breast cancer. Eur J Cancer. 2013;49:2469–2475.Google Scholar
30. de Boer, RH, Baker, C, Speakman, D, et al. The impact of a genomic assay (Oncotype DX) on adjuvant treatment recommendations in early breast cancer. Med J Aust. 2013;199:205–208.Google Scholar
31. Eiermann, W, Rezai, M, Kummel, S, et al. The 21-gene recurrence score assay impacts adjuvant therapy recommendations for ER-positive, node-negative and node-positive early breast cancer resulting in a risk-adapted change in chemotherapy use. Ann Oncol. 2013;24:618–624.Google Scholar
32. Holt, S, Bertelli, G, Humphreys, I, et al. A decision impact, decision conflict and economic assessment of routine OncotypeDX testing of 146 women with node-negative or pNImi, ER-positive breast cancer in the UK. Br J Cancer. 2013;108:2250–2258.Google Scholar
33. Cheung, PS, Tong, AC, Leung, RC, Kwan, WH, Yau, TC. Initial experience with the Oncotype DX assay in decision-making for adjuvant therapy of early oestrogen receptor-positive breast cancer in Hong Kong. Hong Kong Med J. 2014;20:401–406.Google Scholar
34. Fried, G, Moskovitz, M. Treatment decisions in estrogen receptor-positive early breast cancer patients with intermediate oncotype DX recurrence score results. Springerplus. 2014;3:71.Google Scholar
35. Jaafar, H, Bashir, MA, Taher, A, Qawasmeh, K, Jaloudi, M. Impact of Oncotype DX testing on adjuvant treatment decisions in patients with early breast cancer: A single-center study in the United Arab Emirates. Asia Pac J Clin Oncol. 2014;10:354–360.Google Scholar
36. Yamauchi, H, Nakagawa, C, Takei, H, et al. Prospective study of the effect of the 21-gene assay on adjuvant clinical decision-making in Japanese women with estrogen receptor-positive, node-negative, and node-positive breast cancer. Clin Breast Cancer. 2014;14:191-7.Google Scholar
37. Gligorov, JG, Pivot, XB, Jacot, W, et al. Prospective clinical utility study of the use of the 21-gene assay in adjuvant clinical decision making in women with estrogen receptor-positive early invasive breast cancer: Results from the SWITCH Study. Oncologist. 2015;20:873–879.Google Scholar
38. Lee, MH, Han, W, Lee, JE, et al. The clinical impact of 21-gene recurrence score on treatment decisions for patients with hormone receptor-positive early breast cancer in Korea. Cancer Res. 2015;47:208–214.Google Scholar
39. Zhang, YN, Zhou, YD, Mao, F, Sun, Q. Impact of the 21-gene recurrence score assay in adjuvant chemotherapy selection for node-negative, hormone receptor-positive breast cancer in the Chinese population. Neoplasma. 2015;62:658–665.Google Scholar
40. Kuchel, A, Robinson, T, Comins, C, et al. The impact of the 21-gene assay on adjuvant treatment decisions in oestrogen receptor-positive early breast cancer: A prospective study. Br J Cancer. 2016;114:731–736.Google Scholar
41. Levine, MN, Julian, JA, Bedard, PL, et al. Prospective evaluation of the 21-gene recurrence score assay for breast cancer decision-making in Ontario. J Clin Oncol. 2016;34:1065–1071.Google Scholar
42. Ozmen, V, Atasoy, A, Gokmen, E, et al. Impact of Oncotype DX recurrence score on treatment decisions: Results of a prospective multicenter study in Turkey. Cureus. 2016;8:e522.Google Scholar
43. Bueno-De-Mesquita, JM. Use of 70-gene signature to predict prognosis of patients with node-negative breast cancer: A prospective community-based feasibility study (RASTER). Lancet Oncol. 2007;8:1079–1087.Google Scholar
44. Drukker, CA, Bueno-De-Mesquita, JM, Retel, VP, et al. A prospective evaluation of a breast cancer prognosis signature in the observational RASTER study. Int J Cancer. 2013;133:929–936.Google Scholar
45. Gevensleben, H, Gohring, UJ, Buttner, R, et al. Comparison of MammaPrint and TargetPrint results with clinical parameters in German patients with early stage breast cancer. Int J Mol Med. 2010;26:837–843.Google Scholar
46. Hartmann, S, Gerber, B, Elling, D, Heintze, K, Reimer, T. The 70-Gene Signature as prognostic factor for elderly women with hormone receptor-positive, HER2-negative breast cancer. Breast Care. 2012;7:19–24.Google Scholar
47. Cusumano, PG, Generali, D, Ciruelos, E, et al. European inter-institutional impact study of MammaPrint. Breast. 2014;23:423–428.Google Scholar
48. Drukker, CA, van den Hout, HC, Sonke, GS, et al. Risk estimations and treatment decisions in early stage breast cancer: Agreement among oncologists and the impact of the 70-gene signature. Eur J Cancer. 2014;50:1045–1054.Google Scholar
49. Exner, R, Bago-Horvath, Z, Bartsch, R, et al. The multigene signature MammaPrint impacts on multidisciplinary team decisions in ER+, HER2- early breast cancer. Br J Cancer. 2014;111:837–842.Google Scholar
50. Yeo, B, Zabaglo, L, Hills, M, et al. Clinical utility of the IHC4+C score in oestrogen receptor-positive early breast cancer: A prospective decision impact study. Br J Cancer. 2015;113:390–395.Google Scholar
51. Clinical Trials.gov [Internet]. TAILORx trial. Hormone therapy with or without combination chemotherapy in treating women who have undergone surgery for node-negative breast cancer (the TAILORx trial). 2011. http://clinicaltrials.gov/ct2/show/study/NCT00310180?term=oncotype+dx&rank=3 (accessed June 13, 2016).Google Scholar
52. European Organisation for Research and Treatment of Cancer [Internet]. MINDACT trial. Microarray In node negative disease may avoid chemotherapy. A prospective, randomised study comparing the 70-gene expression signature with common clinical-pathological criteria in selecting patients for adjuvant chemotherapy in nodenegative breast cancer. 2011. http://www.eortc.be/services/unit/mindact/MINDACT_websiteii.asp#Current (accessed June 13, 2016).Google Scholar