Literature DB >> 3625256

The importance of histologic grade in long-term prognosis of breast cancer: a study of 1,010 patients, uniformly treated at the Institut Gustave-Roussy.

G Contesso, H Mouriesse, S Friedman, J Genin, D Sarrazin, J Rouesse.   

Abstract

In a study of 1,010 patients with solitary, unilateral, nonmetastatic breast cancer, the histologic grade, assessed by a multifactorial analysis (Cox model) to study its significance with other prognostic factors, was found to be an important, independent factor. For 612 operable patients, two laboratory characteristics, the number of histologically positive nodes and the histologic grade, were the most valuable predictors. These two factors alone form a predictive index that may be an excellent and simple guide for the clinical decision of subsequent therapy. For 398 patients with inoperable breast cancer (ie, tumor greater than or equal to 7 cm, N2-3, inflammatory, skin fixation, and clinically rapidly growing forms), the histologic grade (performed on drill or cutting needle biopsy) was again a most important (and with inflammatory forms the most important) predictor of prognosis in these patients. Our data support that performing our modified histoprognostic grading of Scarff and Bloom is simple, reproducible, incurs no additional cost, may be carried out in the simplest histology laboratory, and finally, defines an important risk factor in all patients. It should be routine for all breast cancer specimens. Furthermore, studies of adjuvant therapy should stratify patients for this variable.

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Mesh:

Year:  1987        PMID: 3625256     DOI: 10.1200/JCO.1987.5.9.1378

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   44.544


  45 in total

Review 1.  Prognostic factors in breast cancer: current and new predictors of metastasis.

Authors:  D F Hayes; C Isaacs; V Stearns
Journal:  J Mammary Gland Biol Neoplasia       Date:  2001-10       Impact factor: 2.673

2.  The Nottingham Prognostic Index in primary breast cancer.

Authors:  M H Galea; R W Blamey; C E Elston; I O Ellis
Journal:  Breast Cancer Res Treat       Date:  1992       Impact factor: 4.872

3.  Prognostic factors and natural history in lymph node-negative breast cancer patients.

Authors:  R Arriagada; L E Rutqvist; L Skoog; H Johansson; A Kramar
Journal:  Breast Cancer Res Treat       Date:  1992       Impact factor: 4.872

4.  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

5.  Epstein-Barr virus (EBV) genome and expression in breast cancer tissue: effect of EBV infection of breast cancer cells on resistance to paclitaxel (Taxol).

Authors:  Hratch Arbach; Viktor Viglasky; Florence Lefeu; Jean-Marc Guinebretière; Vanessa Ramirez; Nadège Bride; Nadia Boualaga; Thomas Bauchet; Jean-Philippe Peyrat; Marie-Christine Mathieu; Samia Mourah; Marie-Pierre Podgorniak; Jean-Marie Seignerin; Kenzo Takada; Irène Joab
Journal:  J Virol       Date:  2006-01       Impact factor: 5.103

Review 6.  Computer-Aided Histopathological Image Analysis Techniques for Automated Nuclear Atypia Scoring of Breast Cancer: a Review.

Authors:  Asha Das; Madhu S Nair; S David Peter
Journal:  J Digit Imaging       Date:  2020-10       Impact factor: 4.056

7.  Prognostic value of proliferation markers expression in breast cancer.

Authors:  Natalija Dedić Plavetić; Jasminka Jakić-Razumović; Ana Kulić; Damir Vrbanec
Journal:  Med Oncol       Date:  2013-03-07       Impact factor: 3.064

8.  Digital pathology image analysis: opportunities and challenges.

Authors:  Anant Madabhushi
Journal:  Imaging Med       Date:  2009

9.  Prognostic value of ki-67 in breast carcinoma: tissue microarray method versus whole section analysis- potentials and pitfalls.

Authors:  Natalija Dedić Plavetić; Jasminka Jakić-Razumović; Ana Kulić; Maja Sirotković-Skerlev; Marina Barić; Damir Vrbanec
Journal:  Pathol Oncol Res       Date:  2014-08-06       Impact factor: 3.201

10.  Molecular-based tumour subtypes of canine mammary carcinomas assessed by immunohistochemistry.

Authors:  Francesco Sassi; Cinzia Benazzi; Gastone Castellani; Giuseppe Sarli
Journal:  BMC Vet Res       Date:  2010-01-28       Impact factor: 2.741

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