Literature DB >> 3618546

Predictors of recurrence and survival of patients with breast cancer.

J Russo, J Frederick, H E Ownby, G Fine, M Hussain, H I Krickstein, T O Robbins, B Rosenberg.   

Abstract

In this study, the characteristics of 646 patient's primary breast carcinomas, including histologic grade (HG), nuclear grade (NG), mitotic grade (MG), final grade (FG), estrogen receptor (E2R) status, and patient's lymph node status (LN) at the time of surgery were correlated with recurrence-free interval and patient survival in order to determine whether any one parameter or group of parameters serve as adequate predictors of tumor behavior and, therefore, patient's prognosis. The authors' results showed that LN, tumor size, and tumor grade were themselves significant predictors of early recurrence and breast cancer death. Each unit increase in LN or MG increased the risk of death by a factor of 1.5 and 2.0, respectively. However, prediction of time to recurrence or death was considerably more accurate when those parameters were used in conjunction, rather than individually. E2R was also significant in predicting death. MG separated patients within a single LN group or E2R group into two subsets having clinically and statistically different prognoses. It was found that patients who had negative lymph nodes and whose tumors were MG1 had a better prognosis than those with MG2,3 tumors; in these latter patients recurrence and death patterns were similar to those of patients with MG1 tumors having one to three positive lymph nodes. Similarly, whereas patients with four or more positive lymph nodes had bad prognoses, those bearing MG1 tumors tended to behave more like those with MG2,3 tumors and having only one to three positive lymph nodes.

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Year:  1987        PMID: 3618546     DOI: 10.1093/ajcp/88.2.123

Source DB:  PubMed          Journal:  Am J Clin Pathol        ISSN: 0002-9173            Impact factor:   2.493


  16 in total

1.  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

2.  Polypeptide composition of normal and neoplastic human breast tissues and cells analyzed by two-dimensional gel electrophoresis.

Authors:  T M Maloney; P L Paine; J Russo
Journal:  Breast Cancer Res Treat       Date:  1989-12       Impact factor: 4.872

Review 3.  Systemic adjuvant therapy for node-negative breast cancer.

Authors:  A D Ginsburg; D J Perrault; K I Pritchard; G P Browman; P B McCulloch; J Skillings
Journal:  CMAJ       Date:  1989-09-01       Impact factor: 8.262

4.  Nucleolar organiser regions: new prognostic variable in breast carcinomas.

Authors:  E Sivridis; B Sims
Journal:  J Clin Pathol       Date:  1990-05       Impact factor: 3.411

5.  INT2 and ERBB2 amplification and ERBB2 expression in breast tumors from patients with different outcomes.

Authors:  R J Pauley; P A Gimotty; T J Paine; P J Dawson; S R Wolman
Journal:  Breast Cancer Res Treat       Date:  1996       Impact factor: 4.872

6.  Histopathologic and dietary prognostic factors for canine mammary carcinoma.

Authors:  F S Shofer; E G Sonnenschein; M H Goldschmidt; L L Laster; L T Glickman
Journal:  Breast Cancer Res Treat       Date:  1989-01       Impact factor: 4.872

7.  Expression of parathyroidlike protein in normal, proliferative, and neoplastic human breast tissues.

Authors:  H Liapis; E C Crouch; L E Grosso; S Kitazawa; M R Wick
Journal:  Am J Pathol       Date:  1993-10       Impact factor: 4.307

8.  Predicting recurrence in axillary-node negative breast cancer patients.

Authors:  D Rosner; W W Lane
Journal:  Breast Cancer Res Treat       Date:  1993       Impact factor: 4.872

9.  Argyrophylic nucleolar organiser regions (AgNOR's) as a prognostic indicator in breast carcinoma.

Authors:  D J Hehir; K J Cronin; P A Dervan; A McCann; D N Carney; W P Hederman; S J Heffernan
Journal:  Ir J Med Sci       Date:  1992-04       Impact factor: 1.568

Review 10.  Prognostic and predictive factors and genetic analysis of early breast cancer.

Authors:  Miguel Martín; Fernando González Palacios; Javier Cortés; Juan de la Haba; José Schneider
Journal:  Clin Transl Oncol       Date:  2009-10       Impact factor: 3.405

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