Nottingham prognostic index plus (NPI+) predicts risk of distant metastases in primary breast cancer.
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.
Division of Cancer and Stem Cells, School of Medicine, Breast Cancer Pathology Research Group, Academic Unit of Oncology, Nottingham City Hospital, University of Nottingham, Hucknall Road, Nottingham, NG5 1PB, UK. andrew.green@nottingham.ac.uk.
Andrew R
AR
Green
Computer Science and Advanced Data Analysis Centre, University of Nottingham, Nottingham, UK.
D
D
Soria
Cellular Pathology, Nottingham University Hospitals NHS Trust, Nottingham, UK.
D G
DG
Powe
Division of Cancer and Stem Cells, School of Medicine, Breast Cancer Pathology Research Group, Academic Unit of Oncology, Nottingham City Hospital, University of Nottingham, Hucknall Road, Nottingham, NG5 1PB, UK.
C C
CC
Nolan
Division of Cancer and Stem Cells, School of Medicine, Breast Cancer Pathology Research Group, Academic Unit of Oncology, Nottingham City Hospital, University of Nottingham, Hucknall Road, Nottingham, NG5 1PB, UK.
M
M
Aleskandarany
Second Department of Pathology, Semmelweis University, Budapest, Hungary.
M A
MA
Szász
Second Department of Pathology, Semmelweis University, Budapest, Hungary.
A M
AM
Tőkés
School of Science and Technology, College of Arts and Science, Nottingham Trent University, Nottingham, UK.
G R
GR
Ball
Computer Science and Advanced Data Analysis Centre, University of Nottingham, Nottingham, UK.
J M
JM
Garibaldi
Division of Cancer and Stem Cells, School of Medicine, Breast Cancer Pathology Research Group, Academic Unit of Oncology, Nottingham City Hospital, University of Nottingham, Hucknall Road, Nottingham, NG5 1PB, UK.|Cellular Pathology, Nottingham University Hospitals NHS Trust, Nottingham, UK.
E A
EA
Rakha
Second Department of Pathology, Semmelweis University, Budapest, Hungary.
J
J
Kulka
Division of Cancer and Stem Cells, School of Medicine, Breast Cancer Pathology Research Group, Academic Unit of Oncology, Nottingham City Hospital, University of Nottingham, Hucknall Road, Nottingham, NG5 1PB, UK.|Cellular Pathology, Nottingham University Hospitals NHS Trust, Nottingham, UK.
I O
IO
Ellis
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000378:metabolism*; D001943:Breast Neoplasms / Q000378:metabolism* / Q000473:pathology*; D066246:ErbB Receptors / Q000378:metabolism; D005260:Female; D006801:Humans; D007633:Keratins / Q000378:metabolism; D008875:Middle Aged; D018396:Mucin-1 / Q000378:metabolism; D009362:Neoplasm Metastasis; D011379:Prognosis; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000378:metabolism; D020893:Receptor, ErbB-3 / Q000378:metabolism; D066247:Receptor, ErbB-4 / Q000378:metabolism; D011960:Receptors, Estrogen / Q000378:metabolism; D016019:Survival Analysis; D016159:Tumor Suppressor Protein p53 / Q000378:metabolism
D014408:Biomarkers, Tumor; D066246:ErbB Receptors; D007633:Keratins; D018396:Mucin-1; D018719:Erb-b2 Receptor Tyrosine Kinases; D020893:Receptor, ErbB-3; D066247:Receptor, ErbB-4; D011960:Receptors, Estrogen; D016159:Tumor Suppressor Protein p53; C495901:TP53 protein, human; C512478:EGFR protein, human; C508053:ERBB2 protein, human; C581292:ERBB3 protein, human; C587689:ERBB4 protein, human
Breast cancer; Classification; Clinical; Molecular; Outcome; Prognostic index