Dataset Information

Nomogram for Predicting Lymph Node Involvement in Triple-Negative Breast Cancer.

ABSTRACT:

Background

Lymph node metastasis of triple-negative breast cancer (TNBC) is essential in treatment strategy formulation. This study aimed to build a nomogram that predicts lymph node metastasis in patients with TNBC.

Materials and methods

A total of 28,966 TNBC patients diagnosed from 2010 to 2017 in the Surveillance, Epidemiology and End Results (SEER) database were enrolled, and randomized 1:1 into the training and validation sets, respectively. Univariate and multivariate logistic regression analysis were applied to identify the predictive factors, which composed the nomogram. The receiver operating characteristic curves showed the efficacy of the nomogram.

Result

Multivariate logistic regression analyses revealed that age, race, tumor size, tumor primary site, and pathological grade were independent predictive factors of lymph node status. Integrating these independent predictive factors, a nomogram was successfully developed for predicting lymph node status, and further validated in the validation set. The areas under the receiver operating characteristic curves of the nomogram in the training and validation sets were 0.684 and 0.689 respectively, showing a satisfactory performance.

Conclusion

We constructed a nomogram to predict the lymph node status in TNBC patients. After further validation in additional large cohorts, the nomogram developed here would do better in predicting, providing more information for staging and treatment, and enabling tailored treatment in TNBC patients.

SUBMITTER: Cui X

PROVIDER: S-EPMC7747752 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Nomogram for Predicting Lymph Node Involvement in Triple-Negative Breast Cancer.

Cui Xiang X Zhu Hao H Huang Jisheng J

Frontiers in oncology 20201204

<h4>Background</h4>Lymph node metastasis of triple-negative breast cancer (TNBC) is essential in treatment strategy formulation. This study aimed to build a nomogram that predicts lymph node metastasis in patients with TNBC.<h4>Materials and methods</h4>A total of 28,966 TNBC patients diagnosed from 2010 to 2017 in the Surveillance, Epidemiology and End Results (SEER) database were enrolled, and randomized 1:1 into the training and validation sets, respectively. Univariate and multivariate logis ...[more]

PMID: 33344259

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Project description:Purpose:Axillary lymph node (ALN) involvement is an important prognostic factor of early invasive breast cancer. The objective of this study was to establish simple nomograms for predicting ALN involvement based on ultrasound (US) characteristics and evaluate the predictive value of US in the detection of ALN involvement. Patients and Methods:A total of 1328 patients with cT1-2N0 breast cancer by physical exam were retrospectively analyzed. Univariate analysis was used for the comparison of variables, and multivariate analysis was performed by binary logistic regression analysis. The R software was used to establish simple nomograms based on the US characteristics alone. The receiver operating characteristic (ROC) curves of the prediction model and the verification group were drawn, and the area under the curve (AUC) was calculated to evaluate the discrimination of the prediction model. A calibration curve was plotted to assess the nomogram predictions vs the actual observations of the ALN metastasis rate and axillary tumor burden rate. Results:The ALN metastasis rates of the training group and the validation group were 35.1% and 34.1%, respectively. Multivariate analysis showed that molecular subtype, lymphovascular invasion, mass descriptors (size, margin, microcalcification and blood flow signal) and LN descriptors (shape, cortical thickness and long-to-short ratio) were independent impact factors in early breast cancer. The AUC of ALN metastasis rate of prediction model based on US features was 0.802, the AUC of high tumor burden rate was 0.873, and the AUC of external validation group was 0.731 and 0.802, respectively. The calibration curve of the nomogram showed that the nomogram predictions are consistent with the actual metastasis rate and the high tumor burden rate. The results showed that preoperative US had a sensitivity of 59.4% and a specificity of 88.9% for predicting the ALN metastasis rate. Conclusion:The successfully established nomograms based on US characteristics to predict ALN metastasis rate and high axillary tumor burden rate in early breast cancer can achieve individual prediction. Compared with other nomogram predictions, it is more intuitive, and can help clinical decision-making; thus, it should be promoted. However, at this time US features alone are insufficient to replace sentinel lymph node biopsy.

Project description:BackgroundDual-targeted therapy is currently the standard adjuvant treatment for human epidermal growth factor receptor 2-positive (HER2+) and lymph node-positive (LN+) breast cancer. However, the optimal therapeutic strategy for patients with HER2+ and lymph node-negative (LN-) breast cancer remains unclear. This population-based study aimed to explore the factors associated with survival in patients with HER2+ and LN- breast cancer, and develop a survival-predicting nomogram in the era of trastuzumab-based single-targeted therapy.MethodsWe collected the clinicopathological information of HER2+ and LN- breast cancer patients who underwent chemotherapy and surgery from The Surveillance, Epidemiology, and End Results (SEER) database (2010-2016, the Trastuzumab-based single-targeted therapy era). We subsequently explored the risk factors for breast cancer-specific survival (BCSS) and overall survival (OS) using a Cox proportional hazards regression model, aiming to identify subgroups with worse prognosis, which would indicate potential demand for dual-targeted therapy. Three- and 5-year survival probability-predictive nomograms were established and subjected to bootstrap internal validation. The concordance index (C-index) and calibration curve were applied to evaluate the performance of the model.ResultsAfter data cleansing, a total of 13,755 patients were included in the current analysis. Using univariate and multivariate Cox proportional hazards regression, higher clinical T stage, hormone receptors-negative (HR-), and partial mastectomy without radiotherapy were identified as independent risk factors for BCSS and OS in patients with HER2+ and LN- breast cancer. Nomograms for 3- and 5-year BCSS and OS incorporating the selected prognostic factors were established. Calibration curves verified good consistency between the actual and nomogram-predicted survival probability. The C-index values of the BCSS and OS predictions and 95% confidence interval (CI) were 0.773 (0.740-0.806) and 0.764 (0.737-0.791), respectively.ConclusionsHigher clinical T stage, HR-, and partial mastectomy without radiotherapy predicted worse prognosis in patients with HER2+ and LN- breast cancer. In clinical practice, patients can be recommended for single-targeted or dual-targeted therapy according to the individualized factors.

Dataset Information

Nomogram for Predicting Lymph Node Involvement in Triple-Negative Breast Cancer.

Background

Materials and methods

Result

Conclusion

Publications

Nomogram for Predicting Lymph Node Involvement in Triple-Negative Breast Cancer.

Similar Datasets

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