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Published in: Breast Cancer Research and Treatment 1/2016

Open Access 01-05-2016 | Preclinical study

Nottingham prognostic index plus (NPI+) predicts risk of distant metastases in primary breast cancer

Authors: Andrew R. Green, D. Soria, D. G. Powe, C. C. Nolan, M. Aleskandarany, M. A. Szász, A. M. Tőkés, G. R. Ball, J. M. Garibaldi, E. A. Rakha, J. Kulka, I. O. Ellis

Published in: Breast Cancer Research and Treatment | Issue 1/2016

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Abstract

The Nottingham prognostic index plus (NPI+) is based on the assessment of biological class combined with established clinicopathologic prognostic variables providing improved patient outcome stratification for breast cancer superior to the traditional NPI. This study aimed to determine prognostic capability of the NPI+ in predicting risk of development of distant disease. A well-characterised series of 1073 primary early-stage BC cases treated in Nottingham and 251 cases from Budapest were immunohistochemically assessed for cytokeratin (Ck)5/6, Ck18, EGFR, oestrogen receptor (ER), progesterone receptor, HER2, HER3, HER4, Mucin 1 and p53 expression. NPI+ biological class and prognostic scores were assigned using individual algorithms for each biological class incorporating clinicopathologic parameters and investigated in terms of prediction of distant metastases-free survival (MFS). The NPI+ identified distinct prognostic groups (PG) within each molecular class which were predictive of MFS providing improved patient outcome stratification superior to the traditional NPI. NPI+ PGs, between series, were comparable in predicting patient outcome between series in luminal A, basal p53 altered and HER2+/ER+ (p > 0.01) tumours. The low-risk groups were similarly validated in luminal B, luminal N, basal p53 normal tumours (p > 0.01). Due to small patient numbers the remaining PGs could not be validated. NPI+ was additionally able to predict a higher risk of metastases at certain distant sites. This study may indicate the NPI+ as a useful tool in predicting the risk of metastases. The NPI+ provides accurate risk stratification allowing improved individualised clinical decision making for breast cancer.
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Literature
2.
go back to reference Galea MH, Blamey RW, Elston CE, Ellis IO (1992) The Nottingham Prognostic Index in primary breast cancer. Breast Cancer Res Treat 22(3):207–219CrossRefPubMed Galea MH, Blamey RW, Elston CE, Ellis IO (1992) The Nottingham Prognostic Index in primary breast cancer. Breast Cancer Res Treat 22(3):207–219CrossRefPubMed
3.
go back to reference Balslev I, Axelsson CK, Zedeler K, Rasmussen BB, Carstensen B, Mouridsen HT (1994) The Nottingham prognostic index applied to 9149 patients from the studies of the Danish Breast Cancer Cooperative Group (DBCG). Breast Cancer Res Treat 32(3):281–290CrossRefPubMed Balslev I, Axelsson CK, Zedeler K, Rasmussen BB, Carstensen B, Mouridsen HT (1994) The Nottingham prognostic index applied to 9149 patients from the studies of the Danish Breast Cancer Cooperative Group (DBCG). Breast Cancer Res Treat 32(3):281–290CrossRefPubMed
4.
go back to reference D’Eredita G, Giardina C, Martellotta M, Natale T, Ferrarese F (2001) Prognostic factors in breast cancer: the predictive value of the Nottingham prognostic index in patients with a long-term follow-up that were treated in a single institution. Eur J Cancer 37(5):591–596CrossRefPubMed D’Eredita G, Giardina C, Martellotta M, Natale T, Ferrarese F (2001) Prognostic factors in breast cancer: the predictive value of the Nottingham prognostic index in patients with a long-term follow-up that were treated in a single institution. Eur J Cancer 37(5):591–596CrossRefPubMed
5.
go back to reference Haybittle JL, Blamey RW, Elston CW, Johnson J, Doyle PJ, Campbell FC et al (1982) A prognostic index in primary breast cancer. Br J Cancer 45(3):361–366CrossRefPubMedPubMedCentral Haybittle JL, Blamey RW, Elston CW, Johnson J, Doyle PJ, Campbell FC et al (1982) A prognostic index in primary breast cancer. Br J Cancer 45(3):361–366CrossRefPubMedPubMedCentral
6.
go back to reference Brown J, Jones M, Benson EA (1993) Comment on the Nottingham prognostic index. Breast Cancer Res Treat 25(3):283CrossRefPubMed Brown J, Jones M, Benson EA (1993) Comment on the Nottingham prognostic index. Breast Cancer Res Treat 25(3):283CrossRefPubMed
7.
go back to reference Blamey RW, Ellis IO, Pinder SE, Lee AH, Macmillan RD, Morgan DA et al (2007) Survival of invasive breast cancer according to the Nottingham prognostic index in cases diagnosed in 1990–1999. Eur J Cancer 43(10):1548–1555CrossRefPubMed Blamey RW, Ellis IO, Pinder SE, Lee AH, Macmillan RD, Morgan DA et al (2007) Survival of invasive breast cancer according to the Nottingham prognostic index in cases diagnosed in 1990–1999. Eur J Cancer 43(10):1548–1555CrossRefPubMed
9.
go back to reference Abd El-Rehim DM, Ball G, Pinder SE, Rakha E, Paish C, Robertson JF et al (2005) High-throughput protein expression analysis using tissue microarray technology of a large well-characterised series identifies biologically distinct classes of breast cancer confirming recent cDNA expression analyses. Int J Cancer 116(3):340–350. doi:10.1002/ijc.21004 CrossRefPubMed Abd El-Rehim DM, Ball G, Pinder SE, Rakha E, Paish C, Robertson JF et al (2005) High-throughput protein expression analysis using tissue microarray technology of a large well-characterised series identifies biologically distinct classes of breast cancer confirming recent cDNA expression analyses. Int J Cancer 116(3):340–350. doi:10.​1002/​ijc.​21004 CrossRefPubMed
13.
go back to reference Green AR, Soria D, Stephen J, Powe DG, Nolan CC, Kunkler I et al (2016) Nottingham prognostic index plus: validation of a clinical decision making tool in breast cancer in an independent series. J Pathol: Clin Res 2(1):32–40 Green AR, Soria D, Stephen J, Powe DG, Nolan CC, Kunkler I et al (2016) Nottingham prognostic index plus: validation of a clinical decision making tool in breast cancer in an independent series. J Pathol: Clin Res 2(1):32–40
15.
go back to reference McCarty KS Jr, Miller LS, Cox EB, Konrath J, McCarty KS Sr (1985) Estrogen receptor analyses. Correlation of biochemical and immunohistochemical methods using monoclonal antireceptor antibodies. Arch Pathol Lab Med 109(8):716–721PubMed McCarty KS Jr, Miller LS, Cox EB, Konrath J, McCarty KS Sr (1985) Estrogen receptor analyses. Correlation of biochemical and immunohistochemical methods using monoclonal antireceptor antibodies. Arch Pathol Lab Med 109(8):716–721PubMed
16.
go back to reference Goulding H, Pinder S, Cannon P et al (1995) A new method for the assessment of oestrogen receptor status on routine formalin-fixed tissue samples. Hum Pathol 26:291–294CrossRefPubMed Goulding H, Pinder S, Cannon P et al (1995) A new method for the assessment of oestrogen receptor status on routine formalin-fixed tissue samples. Hum Pathol 26:291–294CrossRefPubMed
17.
go back to reference Wolff AC, Hammond ME, Schwartz JN, Hagerty KL, Allred DC, Cote RJ et al (2007) American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. J Clin Oncol 25(1):118–145CrossRefPubMed Wolff AC, Hammond ME, Schwartz JN, Hagerty KL, Allred DC, Cote RJ et al (2007) American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. J Clin Oncol 25(1):118–145CrossRefPubMed
18.
go back to reference Garcia-Caballero T, Grabau D, Green AR, Gregory J, Schad A, Kohlwes E et al (2010) Determination of HER2 amplification in primary breast cancer using dual-colour chromogenic in situ hybridization is comparable to fluorescence in situ hybridization: a European multicentre study involving 168 specimens. Histopathology 56(4):472–480. doi:10.1111/j.1365-2559.2010.03503.x CrossRefPubMedPubMedCentral Garcia-Caballero T, Grabau D, Green AR, Gregory J, Schad A, Kohlwes E et al (2010) Determination of HER2 amplification in primary breast cancer using dual-colour chromogenic in situ hybridization is comparable to fluorescence in situ hybridization: a European multicentre study involving 168 specimens. Histopathology 56(4):472–480. doi:10.​1111/​j.​1365-2559.​2010.​03503.​x CrossRefPubMedPubMedCentral
19.
20.
go back to reference Friendly M (2000) Visualizing categorical data. SAS Institute, Cary Friendly M (2000) Visualizing categorical data. SAS Institute, Cary
21.
go back to reference Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M et al (2004) A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 351(27):2817–2826. doi:10.1056/NEJMoa041588 CrossRefPubMed Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M et al (2004) A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 351(27):2817–2826. doi:10.​1056/​NEJMoa041588 CrossRefPubMed
22.
go back to reference van de Vijver MJ, He YD, van’t Veer LJ, Dai H, Hart AA, Voskuil DW et al (2002) A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 347(25):1999–2009. doi:10.1056/NEJMoa021967 CrossRefPubMed van de Vijver MJ, He YD, van’t Veer LJ, Dai H, Hart AA, Voskuil DW et al (2002) A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 347(25):1999–2009. doi:10.​1056/​NEJMoa021967 CrossRefPubMed
24.
go back to reference Ambrogi F, Biganzoli E, Querzoli P, Ferretti S, Boracchi P, Alberti S et al (2006) Molecular subtyping of breast cancer from traditional tumor marker profiles using parallel clustering methods. Clin Cancer Res 12(3 Pt 1):781–790CrossRefPubMed Ambrogi F, Biganzoli E, Querzoli P, Ferretti S, Boracchi P, Alberti S et al (2006) Molecular subtyping of breast cancer from traditional tumor marker profiles using parallel clustering methods. Clin Cancer Res 12(3 Pt 1):781–790CrossRefPubMed
25.
go back to reference Callagy G, Cattaneo E, Daigo Y, Happerfield L, Bobrow LG, Pharoah PD et al (2003) Molecular classification of breast carcinomas using tissue microarrays. Diagn Mol Pathol 12(1):27–34CrossRefPubMed Callagy G, Cattaneo E, Daigo Y, Happerfield L, Bobrow LG, Pharoah PD et al (2003) Molecular classification of breast carcinomas using tissue microarrays. Diagn Mol Pathol 12(1):27–34CrossRefPubMed
26.
go back to reference Perou CM, Jeffrey SS, van de Rijn M, Rees CA, Eisen MB, Ross DT et al (1999) Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proc Natl Acad Sci USA 96(16):9212–9217CrossRefPubMedPubMedCentral Perou CM, Jeffrey SS, van de Rijn M, Rees CA, Eisen MB, Ross DT et al (1999) Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proc Natl Acad Sci USA 96(16):9212–9217CrossRefPubMedPubMedCentral
27.
go back to reference Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H et al (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 98(19):10869–10874CrossRefPubMedPubMedCentral Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H et al (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA 98(19):10869–10874CrossRefPubMedPubMedCentral
28.
go back to reference van ‘t Veer LJ, Dai H, van de Vijver MJ, He HD, Hart AA, Bernards R et al (2003) Expression profiling predicts outcome in breast cancer. Breast Cancer Res 5(1):57–58CrossRefPubMed van ‘t Veer LJ, Dai H, van de Vijver MJ, He HD, Hart AA, Bernards R et al (2003) Expression profiling predicts outcome in breast cancer. Breast Cancer Res 5(1):57–58CrossRefPubMed
29.
30.
go back to reference Parker JS, Mullins M, Cheang MC, Leung S, Voduc D, Vickery T et al (2009) Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 27(8):1160–1167CrossRefPubMedPubMedCentral Parker JS, Mullins M, Cheang MC, Leung S, Voduc D, Vickery T et al (2009) Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 27(8):1160–1167CrossRefPubMedPubMedCentral
31.
go back to reference Darb-Esfahani S, Loibl S, Muller BM, Roller M, Denkert C, Komor M et al (2009) Identification of biology-based breast cancer types with distinct predictive and prognostic features: role of steroid hormone and HER2 receptor expression in patients treated with neoadjuvant anthracycline/taxane-based chemotherapy. Breast Cancer Res 11(5):R69CrossRefPubMedPubMedCentral Darb-Esfahani S, Loibl S, Muller BM, Roller M, Denkert C, Komor M et al (2009) Identification of biology-based breast cancer types with distinct predictive and prognostic features: role of steroid hormone and HER2 receptor expression in patients treated with neoadjuvant anthracycline/taxane-based chemotherapy. Breast Cancer Res 11(5):R69CrossRefPubMedPubMedCentral
Metadata
Title
Nottingham prognostic index plus (NPI+) predicts risk of distant metastases in primary breast cancer
Authors
Andrew R. Green
D. Soria
D. G. Powe
C. C. Nolan
M. Aleskandarany
M. A. Szász
A. M. Tőkés
G. R. Ball
J. M. Garibaldi
E. A. Rakha
J. Kulka
I. O. Ellis
Publication date
01-05-2016
Publisher
Springer US
Published in
Breast Cancer Research and Treatment / Issue 1/2016
Print ISSN: 0167-6806
Electronic ISSN: 1573-7217
DOI
https://doi.org/10.1007/s10549-016-3804-1

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