UpToDate
Official reprint from UpToDate®
www.uptodate.com ©2017 UpToDate, Inc. and/or its affiliates. All Rights Reserved.

Medline ® Abstract for Reference 30

of 'Pathology of breast cancer'

30
TI
Ductal carcinoma in situ of the breast from a population-defined cohort: an evaluation of new histopathological classification systems.
AU
Wärnberg F, Nordgren H, Bergh J, Holmberg L
SO
Eur J Cancer. 1999;35(5):714.
 
The increased incidence of ductal carcinoma in situ of the breast (DCIS) in the era of mammography screening requires a deeper knowledge of the biology of the disease and calls for a suitable classification system to optimise therapy. Our aim was to evaluate the correlation to prognosis for two new classification systems of DCIS. The histopathological specimens from 195 women consecutively diagnosed between 1986 and 1994 with a primary DCIS were re-classified by two separate observers using the system proposed by an European Organization for Research and Treatment of Cancer (EORTC) working group and the Van Nuys system. The relapse-free survival (RFS) by histopathological subgroup and by nuclear grade only was estimated for women treated with breast conserving surgery (n = 149). Thirty-two local recurrences occurred among 149 women (mean follow-up time 59 months). No distant recurrences or breast cancer deaths were reported. The women in the group with the highest differentiation according to the EORTC classification had no recurrences. RFS did not differ appreciably between the two other groups. This was true also after stratification for radiotherapy. We found no statistically significant difference in RFS between the three groups in the Van Nuys classification. There was an overall agreement between the observers in 79% and 64% of the cases, according to the EORTC and Van Nuys systems, respectively. We were able to define one group with highly differentiated lesions and an excellent prognosis with the EORTC classification. Further classification into intermediate and low differentiated lesions did not help predict RFS.
AD
Department of Surgery, University Hospital, Uppsala, Sweden.
PMID