Factors affecting sentinel lymph node metastasis in Turkish breast cancer patients: Predictive value of Ki-67 and the size of lymph node

Özemir, İbrahim Ali; Orhun, Kıvılcım; Eren, Tunç; Baysal, Hakan; Sağıroğlu, Jülide; Leblebici, Metin; Ceyran, Ayse Bahar; Ali̇moğlu, Orhan

doi:10.4149/bll_2016_085

Cited by 8 publications

(9 citation statements)

References 17 publications

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“…In addition, the size of the sentinel node, and the body mass index has been also reported to predict SLNB status (22,23). High differentiation grade (24), mitotic activity (25,26) and lympho-vascular invasion (27) have been also reported.…”

Section: Discussionmentioning

confidence: 96%

Biomarker phenotyping drives clinical management in axillary sentinel node: A retrospective study on women with primary breast cancer in 2002

et al. 2020

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The current study examined if cancer biomarker phenotyping could predict the clinical/pathological status of axillary nodes in women with primary breast cancer. Primary breast cancers from 2002 were analyzed for tumor size, estrogen receptor (ER), progesterone receptor (PgR), Ki-67MIB expression and Her2/neu amplification. Relationships between the clinical and pathological status of the axilla and the biological subtypes classification were analyzed using univariate, multivariate and regression tree analysis. A total of 65% of women with axillary nodes clinically involved had complete axillary node dissection (ALND) while 705 women with clinically negative axillary underwent sentinel lymph node biopsy (SLNB), 18.5% of the latter had at least one pathologically SLNB involved node. Multivariate analysis revealed that the Luminal A subtype was significantly associated (OR 0.62; P<10-9) with clinical negative axilla while HER2pos/not Luminal was associated with clinical positivity (OR 1.71; P<0.01). No significant association between biological subtypes and SLNB status was demonstrated. Regression tree analysis revealed that subgroups with significantly different probability of SLNB status were separated according to tumor size and PgR values. In conclusion, the current study demonstrated that biomarker breast cancer phenotyping is significantly associated with clinical status of axillary nodes but not with pathological involvement of nodes at SLNB. Regression tree analysis could represent a valid attempt to individualize some patients subgroups candidate to different surgical axilla approaches.

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Section: Discussionmentioning

confidence: 96%

Biomarker phenotyping drives clinical management in axillary sentinel node: A retrospective study on women with primary breast cancer in 2002

et al. 2020

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“…( 16 ) validated the clinical value of the MSKCC nomogram based on cases undergoing LNB, with an AUC of 0.722 in predicting the possibility of SLN metastasis. The previous studies had proved that clinicopathological parameters, including lymphovascular invasion, the number of positive SLNs, histological grade, Ki-67 index, and ER/PR status, were independent predictors of SLN metastasis ( 3 – 5 ). Until data regarding the result of clinicopathological parameters after completion of surgery are available, this method of MSKCC nomogram cannot be used as a guide for SLNB.…”

Section: Discussionmentioning

confidence: 99%

“…The correlations between SLN involvement and numerous variables include clinical data (age, primary tumor size, and family history) and histopathological data [lymphovascular invasion, histological grade, estrogen receptor (ER) status, progesterone receptor (PR) status, and Ki-67 proliferation index] were calculated ( 3 – 5 ). However, histopathological information can only be available postoperatively.…”

Section: Introductionmentioning

confidence: 99%

“…Imaging techniques such as ultrasound, CT, dynamic contrast-enhanced MRI (DCE-MRI), and PET are usually used for preoperative assessment in BC detection and ALN status assessment. Among these techniques, DCE-MRI is the best tool to evaluate tumor heterogeneity by analyzing the patterns of enhancement ( 5 ). Recent studies reported that radiomics models based on MRI showed good performance in predicting SLN metastasis in BC patients ( 6 – 9 ).…”

Section: Introductionmentioning

confidence: 99%

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A Radiomics Model for Preoperative Predicting Sentinel Lymph Node Metastasis in Breast Cancer Based on Dynamic Contrast-Enhanced MRI

Jiang

Qin

et al. 2022

Front. Oncol.

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PurposeTo develop a radiomics model based on preoperative dynamic contrast-enhanced MRI (DCE-MRI) to identify sentinel lymph node (SLN) metastasis in breast cancer (BC) patients.Materials and MethodsThe MRI images and clinicopathological data of 142 female primary BC patients from January 2017 to December 2018 were included in this study. The patients were randomly divided into the training and testing cohorts at a ratio of 7:3. Four types of radiomics models were built: 1) a radiomics model based on the region of interest (ROI) of breast tumor; 2) a radiomics model based on the ROI of intra- and peri-breast tumor; 3) a radiomics model based on the ROI of axillary lymph node (ALN); 4) a radiomics model based on the ROI of ALN and breast tumor. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were used to assess the performance of the three radiomics models. The technique for order of preference by similarity to ideal solution (TOPSIS) through decision matrix analysis was used to select the best model.ResultsModels 1, 2, 3, and 4 yielded AUCs of 0.977, 0.999, 0.882, and 1.000 in the training set and 0.699, 0.817, 0.906, and 0.696 in the testing set, respectively, in terms of predicting SLN metastasis. Model 3 had the highest AUC in the testing cohort, and only the difference from Model 1 was statistically significant (p = 0.022). DCA showed that Model 3 yielded a greater net benefit to predict SLN metastasis than the other three models in the testing cohort. The best model analyzed by TOPSIS was Model 3, and the method’s names for normalization, dimensionality reduction, feature selection, and classification are mean, principal component analysis (PCA), ANOVA, and support vector machine (SVM), respectively.ConclusionALN radiomics feature extraction on DCE-MRI is a potential method to evaluate SLN status in BC patients.

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“…Among the biological subtypes, the Her2 (+) group was found to be ranked first with a SLNM rate of 49%. It should be kept in mind that the status of Her2 has been unknown in an important group of patients in studies showing no relationship between Her2 status and SLNM (25).…”

Section: Discussionmentioning

confidence: 99%

Factors Affecting Sentinel Lymph Node Metastasis in Patients With Breast Cancer Undergoing Sentinel Lymph Node Biopsy Before or After Systemi̇c Theraphy

Sağdıç

Yüksel

Çulcu

et al. 2021

ircmj

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The status of axillary lymph node (ALN) along with clinical and histopathological factors is considered an important prognostic factor in invasive breast cancer. The tendency to spread to SLN may differ depending on the biological, clinical and histopathological features of tumors. If we know the factors that affect SLNM, we may not need to perform SLNB in some groups. The aim of the study was to investigate the factors affecting SLNM in patients who underwent surgery and SLNB before (surgery group) or after (neoadjuvant group) systemic theraphy in the light of current biological characteristics of tumors and patients. Methods The study included patients who were operated for breast cancer and underwent SLNB in the general surgery clinic of our institute between January 2017 and August 2019. The study included a total of 1,050 patients, 900 patients in the surgery group and 150 patients in the NAC group. Results In surgery group, multivariate analyses showed that grade III, LVI, Her2 (+) and TN increases the risk of metastasis. In neoadjuvant therapy group, multivariate analyses showed Pre-NAC clinical findings of LN metastasis and luminal A subtypes as effective factors. Conclusions Knowing the factors affecting sentinel lymph node metastasis can provide clues for the type of intervention, reconstruction and RT planning of patients to be operated directly or after neoadjuvant chemotherapy.

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Factors affecting sentinel lymph node metastasis in Turkish breast cancer patients: Predictive value of Ki-67 and the size of lymph node

Cited by 8 publications

References 17 publications

Biomarker phenotyping drives clinical management in axillary sentinel node: A retrospective study on women with primary breast cancer in 2002

Biomarker phenotyping drives clinical management in axillary sentinel node: A retrospective study on women with primary breast cancer in 2002

A Radiomics Model for Preoperative Predicting Sentinel Lymph Node Metastasis in Breast Cancer Based on Dynamic Contrast-Enhanced MRI

Factors Affecting Sentinel Lymph Node Metastasis in Patients With Breast Cancer Undergoing Sentinel Lymph Node Biopsy Before or After Systemi̇c Theraphy

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