Literature DB >> 2551477

Prognostic value of histologic grade nuclear components of Scarff-Bloom-Richardson (SBR). An improved score modification based on a multivariate analysis of 1262 invasive ductal breast carcinomas.

V Le Doussal1, M Tubiana-Hulin, S Friedman, K Hacene, F Spyratos, M Brunet.   

Abstract

We did a multivariate analysis of 1262 patients with operable, invasive ductal breast carcinoma to assess the prognostic value of the Scarff-Bloom-Richardson (SBR) histologic grading system. Nodal metastasis and SBR were the two most important factors for metastasis-free survival (MFS), P = 10-9 and P = 10-5, respectively, for total study time. In patients who were node negative, the SBR and International Union Against Cancer (UICC) stages were the most important for MFS (P = 4 X 10-4 and P = 0.03). In order to try to improve the SBR prognostic value, we first studied the three components of the SBR separately: ductoglandular differentiation proved the least predictive and nuclear pleomorphism and mitotic index the most predictive. A rearrangement of the two nuclear scores alone produced higher risk values and better risk separation of patient subpopulations than SBR, and eliminated the SBR from the multivariate model. This rearrangement, modified SBR (MSBR), defined five new risk subgroups with statistically different risk ratios for MFS (P = 3 X 10-8). SBR grade II (55% of patients) was separated into three MSBR groups significantly different according to MFS (P = 0.008). In the patients who were node negative, MSBR replaced the SBR and was the most important factor for prediction of relapse of MFS (P less than 0.00001). The MSBR is more accurate and predictive than the standard SBR grade and is particularly useful when the nodal status of the patient is negative or unknown.

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Year:  1989        PMID: 2551477     DOI: 10.1002/1097-0142(19891101)64:9<1914::aid-cncr2820640926>3.0.co;2-g

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  65 in total

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Authors:  P J van Diest; G Brugal; J P Baak
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2.  Nuclear pleomorphism, a strong prognostic factor in axillary node-negative small invasive breast cancer.

Authors:  M Stierer; H Rosen; R Weber
Journal:  Breast Cancer Res Treat       Date:  1992-01       Impact factor: 4.872

Review 3.  Utilizing prognostic and predictive factors in breast cancer.

Authors:  Deepa S Subramaniam; Claudine Isaacs
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4.  Scatter factor protein levels in human breast cancers: clinicopathological and biological correlations.

Authors:  Y Yao; L Jin; A Fuchs; A Joseph; H M Hastings; I D Goldberg; E M Rosen
Journal:  Am J Pathol       Date:  1996-11       Impact factor: 4.307

5.  Combined Benefit of Quantitative Three-Compartment Breast Image Analysis and Mammography Radiomics in the Classification of Breast Masses in a Clinical Data Set.

Authors:  Karen Drukker; Maryellen L Giger; Bonnie N Joe; Karla Kerlikowske; Heather Greenwood; Jennifer S Drukteinis; Bethany Niell; Bo Fan; Serghei Malkov; Jesus Avila; Leila Kazemi; John Shepherd
Journal:  Radiology       Date:  2018-12-11       Impact factor: 11.105

6.  Reimagining T Staging Through Artificial Intelligence and Machine Learning Image Processing Approaches in Digital Pathology.

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7.  Personalized medicine in breast cancer: a systematic review.

Authors:  Sang-Hoon Cho; Jongsu Jeon; Seung Il Kim
Journal:  J Breast Cancer       Date:  2012-09-28       Impact factor: 3.588

8.  Immunohistochemical and biochemical measurement of estrogen and progesterone receptors in primary breast cancer. Correlation of histopathology and prognostic factors.

Authors:  M Stierer; H Rosen; R Weber; H Hanak; J Spona; H Tüchler
Journal:  Ann Surg       Date:  1993-07       Impact factor: 12.969

9.  Prognostic value of single nucleotide polymorphisms of candidate genes associated with inflammation in early stage breast cancer.

Authors:  James L Murray; Patricia Thompson; Suk Young Yoo; Kim-Anh Do; Mala Pande; Renke Zhou; Yanhong Liu; Aysegul A Sahin; Melissa L Bondy; Abenaa M Brewster
Journal:  Breast Cancer Res Treat       Date:  2013-03-26       Impact factor: 4.872

10.  Grading invasive ductal carcinoma of the breast: advantages of using automated proliferation index instead of mitotic count.

Authors:  Ossama Tawfik; Bruce F Kimler; Marilyn Davis; Christopher Stasik; Sue-Min Lai; Matthew S Mayo; Fang Fan; John K Donahue; Ivan Damjanov; Patricia Thomas; Carol Connor; William R Jewell; Holly Smith; Carol J Fabian
Journal:  Virchows Arch       Date:  2007-04-26       Impact factor: 4.064

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