A combined nomogram model to preoperatively predict positive sentinel lymph biopsy for breast cancer in Iranian population

Background: Axillary dissection in breast cancer provides useful information on the degree of axillary nodule involvement, which serves as a reliable indicator for the prognosis and staging of breast cancer in patients. The aim of this study was to develop and validate the nomogram model by combining prognostic factors and clinical features to predict the node status of preoperative breast guard positive node cancer. Materials and Methods: Subjects consisted of patients referring to hospitals with the diagnosis of breast cancer. Patients were allowed to substitute molecular subtypes with data on breast cancer diagnosis and prognosis as well as sentinel node status. The bootstrap review was used for internal validation. The predicted performance was evaluated based on the area under the receiver operating characteristic curve. According to the logistic regression analysis, the nomograms reported material strength between predictors and final status reliability. Results: 1172 patients participated in the study, of whom only 539 patients had axillary lymph node involvement. The subtype, family history, calcification, and necrosis were not significantly related to axillary lymph node involvement. Tumor size, histological type, and lymphovascular invasion in multivariate logistic regression were significantly and directly correlated with axillary lymph node involvement. Conclusion: Nomograms, depending on the population, help make decisions to prevent axillary surgery. It seems that the prediction model presented in this study, based on the results of the neuromography, can help surgeons make a more informed decision on underarm surgery. Moreover, in some cases, their surgical program will be informed by accurate medical care and preclusion of major surgeries such as ALND