Literature DB >> 20472825

Prospective evaluation of carcinoembryonic antigen (CEA) and carbohydrate antigen 15.3 (CA 15.3) in patients with primary locoregional breast cancer.

Rafael Molina1, Jose M Auge, Blanca Farrus, Gabriel Zanón, Jaume Pahisa, Montserrat Muñoz, Aureli Torne, Xavier Filella, Jose M Escudero, Pedro Fernandez, Martin Velasco.   

Abstract

BACKGROUND: The utility of carcinoembryonic antigen (CEA) and carbohydrate antigen 15.3 (CA 15.3) as prognostic factors in primary breast cancer is unclear.
METHODS: We prospectively studied CEA and CA 15.3 in the sera of 2062 patients with untreated primary breast cancer diagnosed between 1984 and 2008.
RESULTS: Increased CEA (>5 microg/L) and CA 15.3 (>30 kU/L) concentrations were found in 12.7% and 19.6% of the patients, respectively, and 1 or both tumor markers were increased in 28% (570 of 2062). Increases in each tumor marker correlated with larger tumor sizes and nodal involvement. Tumor size, estrogen receptor (ER), and CEA were independent prognostic factors by multivariate analysis in the total group [disease free survival (DFS) and overall survival (OS)] as well as in node-positive (NP) and node-negative (NN) patients. Nodal involvement and histological grade were independent prognostic factors in the total group as well as in NP patients. By contrast, adjuvant treatment and CA 15.3 were independent prognostic factors only in NN patients (DFS and OS). All patients with CEA >7.5 microg/L had recurrence during follow-up. Use of both tumor markers allowed discrimination of the groups of risk in T1 NN patients: 56.3% of recurrences were seen when 1 or both tumor markers were increased, whereas only 9.4% of recurrences were seen in T1 NN patients without increases of either marker.
CONCLUSIONS: CEA and CA 15.3 are useful prognostic factors in NP and NN breast cancer patients. CEA >7.5 microg/L is associated with a high probability of subclinical metastases.

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Year:  2010        PMID: 20472825     DOI: 10.1373/clinchem.2009.135566

Source DB:  PubMed          Journal:  Clin Chem        ISSN: 0009-9147            Impact factor:   8.327


  28 in total

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10.  Prognostic Models for Nonmetastatic Triple-Negative Breast Cancer Based on the Pretreatment Serum Tumor Markers with Machine Learning.

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