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BMC Cancer ; 20(1): 94, 2020 Feb 03.
Article in English | MEDLINE | ID: mdl-32013960

ABSTRACT

BACKGROUND: Lymphovascular invasion (LVI) is a vital risk factor for prognosis across cancers. We aimed to develop a scoring system for stratifying LVI risk in patients with breast cancer. METHODS: A total of 301 consecutive patients (mean age, 49.8 ± 11.0 years; range, 29-86 years) with breast cancer confirmed by pathological reports were retrospectively evaluated at the authors' institution between June 2015 and October 2018. All patients underwent contrast-enhanced Magnetic Resonance Imaging (MRI) examinations before surgery. MRI findings and histopathologic characteristics of tumors were collected for analysis. Breast LVI was confirmed by postoperative pathology. We used a stepwise logistic regression to select variables and two cut-points were determined to create a three-tier risk-stratification scoring system. The patients were classified as having low, moderate and high probability of LVI. The area under the receiver operating characteristic curve (AUC) was used to evaluate the discrimination ability of the scoring system. RESULTS: Tumor margins, lobulation sign, diffusion-weighted imaging appearance, MRI-reported axillary lymph node metastasis, time to signal intensity curve pattern, and HER-2 were selected as predictors for LVI in the point-based scoring system. Patients were considered at low risk if the score was < 3.5, moderate risk if the score was 3.5 to 6.0, and high risk if the score was ≥6.0. LVI risk was segmented from 0 to 100.0% and was positively associated with an increase in risk scores. The AUC of the scoring system was 0.824 (95% confidence interval [CI]: 0.776--0.872). CONCLUSION: This study shows that a simple and reliable score-based risk-stratification system can be practically used in stratifying the risk of LVI in breast cancer.


Subject(s)
Breast Neoplasms/diagnostic imaging , Diffusion Magnetic Resonance Imaging/methods , Lymphatic Metastasis/diagnostic imaging , Adult , Aged , Aged, 80 and over , Area Under Curve , Female , Humans , Logistic Models , Middle Aged , Neoplasm Invasiveness , Retrospective Studies
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