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Clinical value of serum biomarkers CA153, CEA, and white blood cells in predicting sentinel lymph node metastasis of breast cancer.

Authors: Yuan, Fan; Xiuyuan, Chen; Hongjiang, Li;

Clinical value of serum biomarkers CA153, CEA, and white blood cells in predicting sentinel lymph node metastasis of breast cancer.

Abstract

We retrospectively analyzed preoperative serum CA153, carcinoembryonic antigen (CEA) and white blood cells (WBC) in 121 breast cancer patients who underwent breast-conserving therapy and sentinel lymph node biopsy (SLNB) between June 2017 and April 2019 in our institution. The receiver operating characteristic curve (ROC curve) was used to determine the optional cut-offs of these biomarkers for predicting SLN metastasis. The relationship between the parameters to SLN metastasis of breast cancer was assessed by univariate analysis and multivariate logistic regression models. We finally enrolled 121 breast cancer patients who all underwent SLNB, of whom 56 were confirmed as positive SLN by histopathology. ROC curve analysis calculated an ideal CA153 cutoff value of 7.85 U/ml in prediction of SLN metastasis, with a sensitivity of 73.2%, and specificity of 67.7%. The ideal cutoff value for CEA to predict SLN metastasis was 1.66 ng/ml (sensitivity 67.9%, specificity 73.8%). CA153 combined with CEA showed specificity 78.6% and specificity 76.9%. CA153 and CEA combined with WBC presented sensitivity 80.4% and specificity 78.5%. In the multivariate logistic regression analysis, CA153 (odds ratio (OR): 1.165, 95% confidence interval (CI) 1.061-1.279, P<0.001) and CEA (OR: 3.440, 95% CI: 1.859-6.366, P<0.001) were independent predictive factors of SLN metastasis in patients with breast cancer.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
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Cancer Research