Literature DB >> 17321736

Survival of invasive breast cancer according to the Nottingham Prognostic Index in cases diagnosed in 1990-1999.

R W Blamey1, I O Ellis, S E Pinder, A H S Lee, R D Macmillan, D A L Morgan, J F R Robertson, M J Mitchell, G R Ball, J L Haybittle, C W Elston.   

Abstract

UNLABELLED: The Nottingham Prognostic Index (NPI) is a well established and widely used method of predicting survival of operable primary breast cancer. AIMS: Primary: To present the updated survival figures for each NPI Group. Secondary: From the observations to suggest reasons for the reported fall in mortality from breast cancer.
METHODS: The NPI is compiled from grade, size and lymph node status of the primary tumour. Consecutive cases diagnosed and treated at Nottingham City Hospital in 1980-1986 (n=892) and 1990-1999 (n=2,238) are compared. Changes in protocols towards earlier diagnosis and better case management were made in the late 1980s between the two data sets.
RESULTS: Case survival (Breast Cancer Specific) at 10 years has improved overall from 55% to 77%. Within all Prognostic groups there are high relative and absolute risk reductions. The distribution of cases to Prognostic groups shows only a small increase in the numbers in better groups.
CONCLUSION: The updated survival figures overall and for each Prognostic group for the NPI are presented.

Entities:  

Mesh:

Year:  2007        PMID: 17321736     DOI: 10.1016/j.ejca.2007.01.016

Source DB:  PubMed          Journal:  Eur J Cancer        ISSN: 0959-8049            Impact factor:   9.162


  65 in total

1.  Genetics: How to validate a breast cancer prognostic signature.

Authors:  Paul D Pharoah; Carlos Caldas
Journal:  Nat Rev Clin Oncol       Date:  2010-11       Impact factor: 66.675

2.  The Nottingham Prognostic Index: five- and ten-year data for all-cause survival within a screened population.

Authors:  Y Fong; J Evans; D Brook; J Kenkre; P Jarvis; K Gower-Thomas
Journal:  Ann R Coll Surg Engl       Date:  2015-03       Impact factor: 1.891

3.  [Prognostic and predictive factors of invasive breast cancer: update 2009].

Authors:  T Decker; D Hungermann; W Böcker
Journal:  Pathologe       Date:  2009-02       Impact factor: 1.011

4.  Validation of prognostic indices using the frailty model.

Authors:  C Legrand; L Duchateau; P Janssen; V Ducrocq; R Sylvester
Journal:  Lifetime Data Anal       Date:  2008-07-11       Impact factor: 1.588

5.  Comparison of Oncotype DX® Recurrence Score® with other risk assessment tools including the Nottingham Prognostic Index in the identification of patients with low-risk invasive breast cancer.

Authors:  Maura Bríd Cotter; Alex Dakin; Aoife Maguire; Janice M Walshe; M John Kennedy; Barbara Dunne; Ciarán Ó Riain; Cecily M Quinn
Journal:  Virchows Arch       Date:  2017-07-14       Impact factor: 4.064

6.  Sonographic correlations with the new molecular classification of invasive breast cancer.

Authors:  I T H Au-Yong; A J Evans; S Taneja; E A Rakha; A R Green; C Paish; I O Ellis
Journal:  Eur Radiol       Date:  2009-05-14       Impact factor: 5.315

7.  Clinical outcome data for symptomatic breast cancer: the Breast Cancer Clinical Outcome Measures (BCCOM) Project.

Authors:  T Bates; O Kearins; I Monypenny; C Lagord; G Lawrence
Journal:  Br J Cancer       Date:  2009-07-14       Impact factor: 7.640

8.  One-stop diagnostic breast clinics: how often are breast cancers missed?

Authors:  P Britton; S W Duffy; R Sinnatamby; M G Wallis; S Barter; M Gaskarth; A O'Neill; C Caldas; J D Brenton; P Forouhi; G C Wishart
Journal:  Br J Cancer       Date:  2009-05-19       Impact factor: 7.640

9.  PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer.

Authors:  Gordon C Wishart; Elizabeth M Azzato; David C Greenberg; Jem Rashbass; Olive Kearins; Gill Lawrence; Carlos Caldas; Paul D P Pharoah
Journal:  Breast Cancer Res       Date:  2010-01-06       Impact factor: 6.466

10.  A comprehensive analysis of prognostic signatures reveals the high predictive capacity of the proliferation, immune response and RNA splicing modules in breast cancer.

Authors:  Fabien Reyal; Martin H van Vliet; Nicola J Armstrong; Hugo M Horlings; Karin E de Visser; Marlen Kok; Andrew E Teschendorff; Stella Mook; Laura van 't Veer; Carlos Caldas; Remy J Salmon; Marc J van de Vijver; Lodewyk F A Wessels
Journal:  Breast Cancer Res       Date:  2008-11-13       Impact factor: 6.466

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