PNI as a predictive biomarker: a novel nomogram of immunotherapy efficacy in advanced breast cancer.

PURPOSE

There has been a persistent upward trend in breast cancer (BC) incidence in recent years. The advancement of immunotherapy has introduced promising therapeutic options. This study focuses on identify potential biomarkers to predict clinical outcomes in advanced BC patients receiving immunotherapy.

PATIENTS AND METHODS

In accordance with the predefined inclusion and exclusion criteria, a cohort of 154 patients were enrolled in this study. Progression-free survival (PFS) and overall survival (OS) were the primary endpoints. The end of follow-up is October 2024. Statistical analyses were performed utilizing IBM SPSS Statistics, version 26.0, and R software, version 4.3.1.

RESULTS

Univariate Cox regression analysis demonstrated a statistically significant association between the prognostic nutritional index (PNI) and both PFS and OS (p<0.05). Kaplan-Meier survival analysis, complemented by log-rank tests, revealed statistically differences in survival outcomes stratified by PNI levels (p<0.05). After adjusting for potential confounders in multivariate Cox regression analysis, PNI remained an independent prognostic factor in advanced BC patients undergoing immunotherapy. The predictive accuracy of the nomograms, as measured by the concordance indices (C-indices), was 0.710 for PFS and 0.705 for OS. The area under the ROC (AUC) for the predicted model at 6-, 12-, 18- and 24- months were 0.756, 0.761, 0.684, and 0.779. For OS, the AUC values were 0.753, 0.722, 0.641 and 0.576. The calibration curves revealed good concordance between the observed outcomes and the predicted probabilities.

CONCLUSIONS

PNI is an independent prognostic factor for advanced BC receiving immunotherapy and the prognostic model based on PNI has good discrimination, authenticity and consistency.