Establishment of a logistic regression model nomogram for clinicopathological characteristics and risk factors with axillary lymph node metastasis in T1 locally advanced breast cancer: a retrospective study.

BACKGROUND

Although the research reports on locally advanced breast cancer (LABC) are increasing year by year, there are few reports on T1 LABC axillary lymph node metastasis (ALNM). By establishing a prediction model for T1 LABC ALNM, this study provides a reference value for the probability of ALNM of related patients, which helps clinicians to develop a more effective and individualized treatment plan for LABC.

METHODS

Cases with pathologically confirmed T1 breast cancer (BC) between 2010 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were identified. Logistic regression was used to analyze the correlation between LABC lymph node metastasis and every factor, and the odds ratio (OR) and 95% confidence interval (CI) were used to identify any influencing factors. A nomogram was drawn after incorporating meaningful factors identified in multivariate logistic regression into the model. The receiver operating characteristic (ROC) curve of the model was drawn, and the area under the curve (AUC) and its 95% CI were calculated. Hosmer-Lemeshow goodness-of-fit test and clinical decision curve analysis (DCA) were performed. The results were validated in the validation group.

RESULTS

A total of 200,933 female T1 BC patients were included in this study. Univariate and multivariate logistic regression analysis of T1 BC showed that progesterone receptor (PR)-negative, race, age, lobular carcinoma, micropapillary ductal carcinoma, axillary tail tumor, poor differentiation, and larger tumor diameter increased the probability of ALNM in T1 LABC. A predictive nomogram was established using the above predictors, the AUC of the modeling group was 0.739 (95% CI: 0.732-0.747), and when the AUC cut-off value was 0.026, the specificity and sensitivity of the model were 65.78% and 69.99%, respectively. Validation of the model showed that the AUC of the validation group (n=60,280) was 0.741. When all the risk factors were met, the predicted probability of N2-N3 was 50.40%.

CONCLUSIONS

In this study, it was found that PR-negative, Black race, age, lobular carcinoma, micropapillary ductal carcinoma, axillary tail tumor, poor differentiation, and tumor diameter increased the probability of large lymph node metastasis in T1 LABC small tumors.