ArticleInternational journal of clinical and experimental pathology2020
Clinical value of serum biomarkers CA153, CEA, and white blood cells in predicting sentinel lymph node metastasis of breast cancer.
Article in International journal of clinical and experimental pathology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Nomogram based on deep learning of mammography for the prediction of HER2 expression in breast cancer.Gland surgery · 2026Article
- Development and validation of a non-invasive nomogram for predicting bone metastasis in newly diagnosed breast cancer.Translational cancer research · 2026Article
- Development and validation of a nomogram for predicting axillary reverse mapping lymph node metastasis in breast cancer patients.Frontiers in oncology · 2026Article
- The role of serum acsl4 in differentiating early-stage breast cancer.European journal of medical research · 2025Observational
- Development and validation of a radiomics-based nomogram for predicting two subtypes of HER2-negative breast cancer.Gland surgery · 2024Article
- New Insight for Axillary De-Escalation in Breast Cancer Surgery: "SoFT Study" Retrospective Analysis.Current oncology (Toronto, Ont.) · 2024Article
- Tumor biomarkers for diagnosis, prognosis and targeted therapy.Signal transduction and targeted therapy · 2024Review
- Predictive value of CA-153, CA-125 and Apo A for ocular metastasis in menopausal female patients with breast cancer.International journal of ophthalmology · 2024Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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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33284901PMC7716139W3112583703What OpenQuestion holds
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