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. 1998 Feb;16(2):462-9.
doi: 10.1200/JCO.1998.16.2.462.

Prognostic and predictive value of c-erbB-2 overexpression in primary breast cancer, alone and in combination with other prognostic markers

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Prognostic and predictive value of c-erbB-2 overexpression in primary breast cancer, alone and in combination with other prognostic markers

S Sjögren et al. J Clin Oncol. 1998 Feb.

Abstract

Purpose: To investigate the prognostic and predictive value of c-erbB-2 overexpression in breast cancer in relation to other prognostic markers.

Patients and methods: Paraffin-embedded tumors from 315 consecutive primary breast cancer patients were screened for c-erbB-2 protein (p185) overexpression by immunohistochemistry using the monoclonal antibody CB11.

Results: c-erbB-2 protein overexpression was detected in 19% of tumors and was associated with shorter 5-year overall survival (OAS) rate compared with c-erbB-2-negative cases in the total patient material (58% and 77%, respectively; P = .004) and in the 96 node-positive patients (31% and 61%, respectively; P = .02), but not in node-negative patients. For 47 node-positive patients treated with adjuvant tamoxifen and radiotherapy, the 5-year OAS was 13% for c-erbB-2 overexpression and 75% for c-erbB-2-negative patients (P = .00004). The frequency of c-erbB-2 overexpression decreased with age at diagnosis. The prognostic value of c-erbB-2 on OAS was independent of age, node status, tumor size, histopathologic grade, hormone receptor status, S phase, p53 status, and adjuvant treatment. c-erbB-2 status added prognostic information to p53-negative and low S-phase cases, but not to p53-positive and high S-phase cases. Correspondingly, these only added information to c-erbB-2-negative cases.

Conclusion: c-erbB-2 protein overexpression may have a predictive value with regard to adjuvant therapy in node-positive patients, for whom adjuvant tamoxifen with radiotherapy appears insufficient in the presence of c-erbB-2 overexpression. Combination of conventional and newer tumor markers may identify patients with a worse prognosis within groups with a generally favorable prognosis.

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