A nomogram with Nottingham prognostic index for predicting locoregional recurrence in breast cancer patients

The Nottingham prognostic index (NPI) has been shown to negatively impact survival in breast cancer (BC). However, its ability to predict the locoregional recurrence (LRR) of BC remains still unclear. This study aims to determine whether a higher NPI serves as a significant predictor of LRR in BC.

In total, 238 patients with BC were included in this analysis, and relevant clinicopathological features were collected. Correlation analysis was performed between NPI scores and clinicopathological characteristics. The optimal nomogram model was determined by Akaike information criterion. The accuracy of the model's predictions was evaluated using receiver operating characteristic curves (ROC curves), calibration curves and goodness of fit tests. The clinical application value was assessed through decision curve analysis.

Six significant variables were identified, including age, body mass index (BMI), TNM stage, NPI, vascular invasion, perineural invasion (P<0.05). Two prediction models, namely a TNM-stage-based model and an NPI-based model, were constructed. The area under the curve (AUC) for the TNM-stage- and NPI-based models were 0.843 (0.785,0.901) and 0.830 (0.766,0.893) in training set and 0.649 (0.520,0.778) and 0.728 (0.610,0.846) in validation set, respectively. Both models exhibited good calibration and goodness of fit. The F-measures were 0.761vs 0.756 and 0.556 vs 0.696, respectively. Clinical decision curve analysis showed that both models provided clinical benefits in evaluating risk judgments based on the nomogram model.

a higher NPI is an independent risk factor for predicting LRR in BC. The nomogram model based on NPI demonstrates good discrimination and calibration, offering potential clinical benefits. Therefore, it merits widespread adoption and application.