Development and internal validation of a nomogram for predicting neoadjuvant therapy efficacy in breast cancer based on the HALP score.

Background: Hemoglobin-albumin-lymphocyte-platelet (HALP) score is a composite index reflecting patients' immune, nutritional, and inflammatory status, which has been associated with breast cancer prognosis. However, its value in predicting neoadjuvant therapy (NAT) efficacy in the overall breast cancer population remains controversial and understudied. This study aims to explore the relationship between preoperative HALP score and NAT efficacy in breast cancer patients and develop a predictive nomogram. Methods: Clinicopathological data of 314 breast cancer patients who received NAT and mastectomy between January 2013 and November 2024 were retrospectively collected. Propensity score matching (PSM) was used to balance baseline characteristics between high-HALP and low-HALP groups. A nomogram was constructed based on multivariate Logistic regression analysis. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used to evaluate the model's performance. Kaplan-Meier curves were applied to compare disease-free survival (DFS) and overall survival (OS) between groups before and after PSM, as well as between different point stratification groups based on the nomogram. Results: After PSM, 226 patients were included, with 113 in each group. Multivariate Logistic regression confirmed that a low HALP score was an independent negative predictor of pathological complete response (pCR, defined as ypT0/is ypN0) [odds ratio (OR) =0.42, 95% confidence interval (CI): 0.19-0.92, P=0.03], while positive human epidermal growth factor receptor-2 (HER2) status was an independent positive predictor (OR =5.00, 95% CI: 1.93-12.92, P<0.001). A higher preoperative HALP score was correlated with a greater likelihood of achieving pCR, whereas a low HALP score was associated with a lower pCR rate and poorer long-term prognosis in breast cancer patients. The nomogram integrating HALP score, HER2, estrogen receptor (ER), progesterone receptor (PR), N stage, and grade showed area under the curve (AUC) values of 0.80 (95% CI: 0.73-0.87) in the training cohort and 0.78 (95% CI: 0.66-0.91) in the validation cohort. Notably, only internal validation via random data splitting was conducted in this study, and no external validation was performed. Calibration curves demonstrated good consistency between predicted and actual pCR probabilities, and DCA confirmed favorable clinical utility. Kaplan-Meier analysis showed that the high-HALP group had significantly better DFS and OS both before and after PSM (all P<0.05), and the low-point group based on nomogram scores had longer DFS and OS (all P<0.05). Conclusions: Preoperative low HALP score is associated with lower pCR rate and poorer prognosis in breast cancer patients. The nomogram based on HALP score combined with PSM provides a reliable tool for predicting NAT efficacy and individualized treatment decision-making in breast cancer.