Nomogram for predicting preoperative regional lymph nodes metastasis in patients with metaplastic breast cancer: a SEER population-based study

Abstract

Background: Metaplastic breast cancer (MBC) is a rare subtype of breast cancer, and generally associated with poor outcomes. Lymph nodes metastasis (LNM) is confirmed as a critical independent prognostic factor and determine the optimal treatment strategies in MBC patients. We aimed to develop and validate a nomogram to predict the possibility of preoperative regional LNM in MBC patients.

Methods: MBC patients diagnosed between 1990 and 2016 in the Surveillance, Epidemiology, and End Results (SEER) database were included and stochastically divided into a training set and validation set at a ratio of 7:3. The risk variables of regional LNM in the training set were determined by univariate and multivariate logistic regression analyses. And then we integrated those risk factors to construct the nomogram. The prediction nomogram was further verified in the verification set. The discrimination, calibration and clinical utility of the nomogram were evaluated by the area under the receiver operating characteristic (ROC) curve (AUC), calibration plots and decision curve analysis (DCA), respectively.

Results: A total of 2205 female MBC patients were included in the study. Among the 2205 patients, 24.8% (546/2205) had positive regional lymph nodes. The nomogram for predicting the risk of regional LNM contained predictors of grade, estrogen receptor (ER) status and tumor size, with AUC of 0.683 (95% confidence interval (CI): 0.653-0.713) and 0.667 (95% CI: 0.621-0.712) in the training and validation sets, respectively. Calibration plots showed perfect agreement between actual and predicted regional LNM risks. At the same time, DCA of the nomogram demonstrated good clinical utilities.

Conclusions: The nomogram established in this study showed excellent prediction ability, and could be used to preoperatively estimate the regional LNM risk in MBC.

Keywords: Breast cancer; Lymph nodes metastasis; Metaplastic breast cancer; Nomogram; SEER.

Fig. 1

Patient enrollment and exclusion process in the SEER database

Fig. 2

Nomogram predicting regional LNM in patients with MBC based on training cohort. The first row is the point assignment for each variable. Rows 2–4 indicate the variables included in the nomogram. For an individual patient, each variable is assigned a point value based on the histopathological characteristics. The points for each variable were summed and located on the total point line. And then, the bottom line shows the probability of the patient having regional LNM

Fig. 3

Receiver operating characteristics analyses of the nomogram of model and other predictors (grade, ER status and tumor size) based on the training (a) and validation (b) cohorts

Fig. 4

Internal (a) and external (b) calibration plots of the nomogram for predicting regional LNM in patients with MBC

Fig. 5

Decision curve for prediction of regional LNM for MBC. Black line: assume no patient will have regional LNM; gray line: assume all patients will have regional LNM; orange line: binary decision rule based on ER status alone; green line: binary decision rule based on grade alone; blue line: binary decision rule based on tumor size alone; red line: decision based on nomogram. The x-axis and the y-axis were the threshold probability and the net benefit, respectively