Predictive Factors for Nonsentinel Lymph Node Metastasis in Patients With Positive Sentinel Lymph Nodes After Neoadjuvant Chemotherapy: Nomogram for Predicting Nonsentinel Lymph Node Metastasis

Ryu, Jai Min; Lee, Se Kyung; Kim, Ji Young; Yu, Jonghan; Kim, Seok Won; Lee, Jeong Eon; Han, Se Hwan; Jung, Yongsik; Nam, Seok Jin

doi:10.1016/j.clbc.2017.03.014

Cited by 23 publications

(22 citation statements)

References 27 publications

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“…Although previous studies suggested that pathological T stage, lymphovascular invasion, or extracapsular extension were significantly associated with the metastasis of non-SLNs, 17,18 we excluded these from the analysis of this study as they could not be determined prior to breast surgery. In our medical center, all patients with breast cancer undergo preoperative AUS owing to its convenience and specificity.…”

Section: Discussionmentioning

confidence: 99%

“…Similarly, numerous previous studies have demonstrated the significant association between SLNM number and non-SLN metastasis. 17,18,33 Furthermore, some clinical trials have reported a significant decrease in the FNRs with an increasing number of resected SLNs. 5,14 Thus, nodal status prior to NAC and SLNM number were identified as the risk factors of non-SLN metastasis (OR: 2.867, p=0.018 for nodal status prior to NAC, OR: 2.800, p<0.001 for SLNM number), while SLN number was identified as the protective factor of non-SLN metastasis (OR: 0.514, p<0.001).…”

Section: Discussionmentioning

confidence: 99%

“…Several models have been introduced in previous studies. [16][17][18] However, these models included factors that could only be determined after breast surgery, such as pathological T stage, lymphovascular invasion, and extracapsular extension. Thus, they could not be used to facilitate the selection of patients who could avoid unnecessary ALND.…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, several models have been developed to predict the risk of non-SLN metastasis in patients with breast cancer receiving NAC. [16][17][18] Unfortunately, these models have limited value with an adjusted area under the receiver operating characteristic curve (AUC) <0.8. Thus, the development of a new predictive model with excellent discriminatory power is warranted.…”

Section: Introductionmentioning

confidence: 99%

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<p>A New Model Incorporating Axillary Ultrasound After Neoadjuvant Chemotherapy to Predict Non-Sentinel Lymph Node Metastasis in Invasive Breast Cancer</p>

Zhang

Zhu

Sheng

et al. 2020

CMAR

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These authors contributed equally to this workPurpose: Few models with good discriminative power have been introduced to predict the risk of non-sentinel lymph node (non-SLN) metastasis in breast cancer after neoadjuvant chemotherapy (NAC). We aimed to develop a new and simple model for predicting the probability of non-SLN metastasis in breast cancer and facilitate the selection of patients who could avoid unnecessary axillary lymph node dissection following NAC. Patients and Methods: A total of 298 patients diagnosed with invasive breast cancer, who underwent SLN biopsy after completing NAC and subsequently breast surgery, were included and classified into the training set (n=228) and testing set (n=70). Univariate and multivariate analyses were used to select factors that could be determined prior to breast surgery and significantly correlated with non-SLN metastasis in the training set. A logistic regression model was developed based on these factors and validated in the testing set. Results: Nodal status before NAC, post-NAC axillary ultrasound status, SLN number, and SLN metastasis number were independent predictors of non-SLN metastases in breast cancer after NAC. A predictive model based on these factors yielded an area under the curve of 0.838 (95% confidence interval: 0.774-0.902, p< 0.001) in the training set. When applied to the testing set, this model yielded an area under the curve of 0.808 (95% confidence interval: 0.609-1.000, p= 0.003). Conclusion:A new and simple model, which incorporated factors that could be determined prior to breast surgery, was developed to predict non-SLN metastasis in invasive breast cancer following NAC. Although this model performed excellently in internal validation, it requires external validation before it can be widely utilized in the clinical setting.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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<p>A New Model Incorporating Axillary Ultrasound After Neoadjuvant Chemotherapy to Predict Non-Sentinel Lymph Node Metastasis in Invasive Breast Cancer</p>

Zhang

Zhu

Sheng

et al. 2020

CMAR

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“…[2][3][4][5][6] Studies have revealed that LVI status facilitates the selection of an optimal therapeutic strategy for individual breast cancer patients. [7][8][9][10][11] The extent of LVI is an important factor for predicting neoadjuvant chemotherapy (NAC) efficacy. 7 This suggests that LVI may identify chemoresistant patients before NAC.…”

mentioning

confidence: 99%

Preoperative prediction of lymphovascular invasion in invasive breast cancer with dynamic contrast‐enhanced‐MRI‐based radiomics

Liu

Bao

et al. 2019

Magnetic Resonance Imaging

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Background Lymphovascular invasion (LVI) status facilitates the selection of optimal therapeutic strategy for breast cancer patients, but in clinical practice LVI status is determined in pathological specimens after resection. Purpose To explore the use of dynamic contrast‐enhanced (DCE)‐magnetic resonance imaging (MRI)‐based radiomics for preoperative prediction of LVI in invasive breast cancer. Study Type Prospective. Population Ninety training cohort patients (22 LVI‐positive and 68 LVI‐negative) and 59 validation cohort patients (22 LVI‐positive and 37 LVI‐negative) were enrolled. Field Strength/Sequence 1.5 T and 3.0 T, T1‐weighted DCE‐MRI. Assessment Axillary lymph node (ALN) status for each patient was evaluated based on MR images (defined as MRI ALN status), and DCE semiquantitative parameters of lesions were calculated. Radiomic features were extracted from the first postcontrast DCE‐MRI. A radiomics signature was constructed in the training cohort with 10‐fold cross‐validation. The independent risk factors for LVI were identified and prediction models for LVI were developed. Their prediction performances and clinical usefulness were evaluated in the validation cohort. Statistical Tests Mann–Whitney U‐test, chi‐square test, kappa statistics, least absolute shrinkage and selection operator (LASSO) regression, logistic regression, receiver operating characteristic (ROC) analysis, DeLong test, and decision curve analysis (DCA). Results Two radiomic features were selected to construct the radiomics signature. MRI ALN status (odds ratio, 10.452; P < 0.001) and the radiomics signature (odds ratio, 2.895; P = 0.031) were identified as independent risk factors for LVI. The value of the area under the curve (AUC) for a model combining both (0.763) was higher than that for MRI ALN status alone (0.665; P = 0.029) and similar to that for the radiomics signature (0.752; P = 0.857). DCA showed that the combined model added more net benefit than either feature alone. Data Conclusion The DCE‐MRI‐based radiomics signature in combination with MRI ALN status was effective in predicting the LVI status of patients with invasive breast cancer before surgery. Level of Evidence: 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:847–857.

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Nonsentinel lymph node metastases in cases of micrometastasis detected by sentinel lymph node biopsy after neoadjuvant chemotherapy

Shin,

Ryu,

Lee

et al. 2024

Cancer

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BackgroundThere is a clinical need to omit axillary lymph node dissection (ALND) when residual disease in sentinel lymph nodes (SLNs) is low after neoadjuvant chemotherapy (NAC). This study aimed to clarify the relationship between micrometastasis in SLNs after NAC and additional non‐SLN metastases by analyzing SLN biopsy results followed by ALND.MethodsThis retrospective study reviewed clinical records of patients who underwent breast cancer surgery between January 2010 and June 2022 after NAC at Samsung Medical Center. Of 3944 patients, 806 underwent SLN biopsy followed by ALND. Intraoperative frozen SLN biopsy results were examined, including the number and size of metastases in SLNs, and further investigated the number of additional non‐SLN metastases.ResultsAmong the 806 patients, 95 (11.8%) had micrometastasis on SLNs in frozen sections, of which 89 (93.7%) had clinically node‐positive (cN1‐3) breast cancer before NAC. Twenty‐three patients (24.2%) exhibited positive additional non‐SLNs after ALND. The presence of lymphovascular invasion (vs. absence; odds ratio [OR] = 4.02, p = .0151) and having two or more SLNs with micrometastasis (vs. a positive SLN; OR = 3.65, p = .0301) were significantly associated with additional non‐SLN metastases. Tumor subtypes and breast pathological complete response after NAC showed no correlation with the additional non‐SLN metastases.ConclusionThe study identified a 24.2% possibility of additional non‐SLN metastasis if micrometastases was detected in the SLN after NAC. This rate is significant, indicating that ALND cannot be omitted if low volume residual disease, such as micrometastasis, is identified in the SLN after NAC.

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Predictive Factors for Nonsentinel Lymph Node Metastasis in Patients With Positive Sentinel Lymph Nodes After Neoadjuvant Chemotherapy: Nomogram for Predicting Nonsentinel Lymph Node Metastasis

Cited by 23 publications

References 27 publications

<p>A New Model Incorporating Axillary Ultrasound After Neoadjuvant Chemotherapy to Predict Non-Sentinel Lymph Node Metastasis in Invasive Breast Cancer</p>

<p>A New Model Incorporating Axillary Ultrasound After Neoadjuvant Chemotherapy to Predict Non-Sentinel Lymph Node Metastasis in Invasive Breast Cancer</p>

Preoperative prediction of lymphovascular invasion in invasive breast cancer with dynamic contrast‐enhanced‐MRI‐based radiomics

Nonsentinel lymph node metastases in cases of micrometastasis detected by sentinel lymph node biopsy after neoadjuvant chemotherapy

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