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A nomogram to predict the probability of axillary lymph node metastasis in female patients with breast cancer in China: A nationwide, multicenter, 10-year epidemiological study. | LitMetric

AI Article Synopsis

  • The study aimed to create a predictive model for axillary lymph node metastasis in breast cancer patients to inform surgical decisions, reducing unnecessary procedures.
  • The analysis involved 4211 female breast cancer patients from seven centers in China, using various clinical factors to identify independent predictors of metastasis for the model.
  • The developed nomogram demonstrated strong predictive capabilities, suggesting that if the predicted risk is under 20%, sentinel lymph node biopsy might not be necessary, potentially leading to less invasive surgical options in the future.

Article Abstract

Axillary lymph node dissection (ALND) or sentinel lymph node biopsy (SLNB) alone may lead to postoperative complications. Among patients with positive ALN in the preoperative examination, approximately 40% patients do not have SLN metastasis. Herein, we aimed to develop a model to predict the probability of ALN metastasis as a preoperative tool to support clinical decision-making. We retrospectively analyzed the clinicopathological features of 4211 female patients with breast cancer who were diagnosed in seven breast cancer centers representing entire China, over 10 years (1999-2008). The patients were randomly categorized into a training cohort or validation cohort (3:1 ratio). Multivariate logistic regression analysis was performed for 1869 patients with complete information on the study variables. Age at diagnosis, tumor size, tumor quadrant, clinical nodal status, local invasion status, pathological type, and molecular subtypes were the independent predictors of ALN metastasis. The nomogram was then developed using the seven variables. Further, it was subsequently validated in 642 patients with complete data on variables in the validation cohort. Coefficient of determination (R²) and the area under the receiver-operating characteristic (ROC) curve (AUC) were calculated to be 0.979 and 0.7007, showing good calibration and discrimination of the model, respectively. The false-negative rates of the nomogram were 0 and 6.9% for the predicted risk cut-off values of 14.03% and 20%, respectively. Therefore, when the predicted risk is less than 20%, SLNB may be avoided. After further validation in various patient populations, this model may support increasingly limited axillary surgery in breast cancer.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5471057PMC
http://dx.doi.org/10.18632/oncotarget.13330DOI Listing

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