The early prediction of neoadjuvant chemotherapy (NAC) efficacy is essential for the timely modification of treatment regimens. This study investigates the clinical utility of integrating ultrasound examination with the nutritional risk index (NRI) to predict pathological complete response (pCR) in breast cancer patients following NAC. Utilizing a retrospective analysis, we examined data from 85 breast cancer patients who underwent NAC between January 2020 and December 2023. All participants received routine ultrasound evaluations and NRI assessments both prior to NAC initiation and after the completion of 2 treatment cycles. Based on the Miller–Payne grading system, patients were categorized into the pCR group (39 cases) and the non-pCR group (46 cases). Significant variables ( P < .05) were identified through univariate logistic regression analysis and subsequently incorporated into a multivariate binary logistic regression model (inclusion criterion: P < .20). The diagnostic performance was assessed using the receiver operating characteristic curve, while the calibration curve was utilized to further evaluate the predictive value. The multivariate analysis identified 3 independent predictors of pathological complete response (pCR): N stage (N2: odds ratio OR = 3.68, 95% confidence interval CI: 1.08–12.53, P = .037), change in tumor maximum diameter after the second neoadjuvant chemotherapy (NAC) cycle (ΔD2; OR = 0.95, 95% CI: 0.92–0.99, P = .024), and change in nutritional risk index after the second NAC cycle (ΔNRI2; OR = 1.10, 95% CI: 1.01–1.19, P = .032). The variance inflation factor values (ranging from 1.070 to 1.163) indicated an absence of multicollinearity. The combined diagnostic model achieved an area under the receiver operating characteristic curve of 0.847 (95% CI: 0.765–0.930), with a sensitivity of 69.2% and a specificity of 89.1%. The calibration curve demonstrated strong agreement between predicted and actual outcomes (Hosmer–Lemeshow test, P = .747). The integration of N stage, ΔD2, and ΔNRI2 exhibits significant clinical utility for the early prediction of NAC efficacy in breast cancer, potentially informing treatment adjustments and enhancing patient outcomes. However, the study’s small sample size (n = 85) and single-center retrospective design constrain its generalizability. Therefore, large-scale, multicenter prospective validation is necessary prior to clinical implementation.
Liu et al. (Fri,) studied this question.