Predictive Value of Histopathological Variables and Peripheral Immune-Inflammatory Markers in De Novo Metastatic Breast Cancer: Development and Clinical Utility of the Novel KiTNASP Score - Serkan Yilmaz; Mesut Yur; Erhan Aygen; Yavuz Selim İlhan; Ahmet Akbaş; Şafak Özer Balin; Ali Rıza Avul (Biomedicines, 2026)
Background and Aim: Approximately 10% of breast cancer patients present with distant organ metastases at initial diagnosis. This study aimed to evaluate the efficacy of immune-inflammatory markers and histopathological variables in identifying de novo metastatic breast cancer. Methods: Patients with breast cancer referred to a tertiary surgical oncology clinic between January 2020 and December 2022 were retrospectively screened. A total of 412 patients met the strict inclusion criteria. Laboratory parameters and radiological findings obtained during the initial diagnostic workup, prior to the initiation of any therapeutic intervention, were comprehensively evaluated. Results: Among the screened cohort, 56 patients presented with synchronous distant organ metastases at diagnosis. Significant differences (p < 0.05) were observed between the metastatic and non-metastatic groups in serum hemoglobin, albumin, and alkaline phosphatase (ALP) levels, lymphocyte and neutrophil counts, hemoglobin-albumin-lymphocyte-platelet score, prognostic nutritional index (PNI), systemic immune-inflammation index (SII), monocyte-to-lymphocyte ratio, platelet-to-lymphocyte ratio, neutrophil-to-lymphocyte ratio, and pan-immune-inflammation value. Multivariate logistic regression analysis identified Ki-67, T stage, N stage, ALP, SII, and PNI as independent predictors of metastasis (p < 0.05). In the receiver operating characteristic (ROC) analysis, the prognostic score formulated from this predictive model demonstrated an area under the curve (AUC) of 0.821 (95% CI: 0.781–0.857, p < 0.001, and Z-score = 9.34). At an optimal cut-off value of >0.233, the score yielded a sensitivity of 64.3% and a specificity of 92.1%. Furthermore, Decision Curve Analysis (DCA) confirmed a positive net clinical benefit across the decision-making threshold. Conclusions: The developed prognostic score may be a promising clinical tool for differentiating de novo metastatic breast cancer from non-metastatic disease at initial staging. This non-invasive approach may help clinicians risk-stratify patients, reduce diagnostic delays, and optimize early intervention strategies. Nonetheless, larger prospective multicenter studies are warranted for robust validation.