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Breast Cancer Res Treat. 1997 Jan;42(2):149-63.

Validation of existing and development of new prognostic classification schemes in node negative breast cancer. German Breast Cancer Study Group.

Author information

1
Institute of Medical Biometry and Informatics, University of Freiburg, Germany. wfs@imbi.uni.freiburg.de

Erratum in

  • Breast Cancer Res Treat 1998 Mar;48(2):191-2.

Abstract

Several prognostic classification schemes in node negative breast cancer are proposed, but only the Nottingham Prognostic Index (NPI) seems to be sufficiently validated. Validation, which is a prerequisite for a sensible assessment, is not published for two recent proposals according to Glick et al. [1] and Rubens [2]. The German Breast Cancer Study Group (GBSG) entered 662 eligible patients in a prospective observational study. 603 of them had complete data for seven 'standard' prognostic factors and median follow-up is about 5 years. As there is no accepted and informative measure of separation for classification schemes presently available, we propose a new one and use it additionally to the well known logrank-test and Kaplan-Meier estimates to investigate the predictive power of the three schemes. significant differences in survival and recurrence-free survival could be established for the NPI subgroups but not for others where even the ordering of the groups was different. With the Cox model and the classification and regression tree approach we develop two new proposals for the differentiation of subgroups of node negative patients. As in the NPI, tumor size and grade are the most important factors, but with a different weighting scheme. Young age (< or = 40 years) and very high estrogen receptor values (> 300 fmol) in a small subgroup of patients were associated with worse prognosis. The new proposals showed a better degree of separation, which demonstrates that an improvement seems possible using standard factors. Because the measures of separation give an overoptimistic impression for the new proposals, a validation with other studies is necessary before a general recommendation can be given.

PMID:
9138604
DOI:
10.1023/a:1005733404976
[Indexed for MEDLINE]

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