Purpose: Predicting response to neoadjuvant therapy (NAT) remains a clinical challenge in patients with HER2-positive breast cancer (BC). Systemic inflammatory and immune-nutritional biomarkers have emerged as potential predictors of treatment response; however, their value in patients receiving dual anti-HER2 therapy is not well defined. Patients and Methods: This retrospective study included patients with HER2-positive BC treated with neoadjuvant dual anti-HER2 therapy between January 2023 and February 2025. A total of 136 patients were included. Pathological complete response (pCR) and radiological response assessed by positron emission tomography/computed tomography (PET/CT) were the primary outcomes. Routinely available inflammatory and immune-nutritional indices, including lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII), and C-reactive protein–to–albumin ratio (CAR), were evaluated using receiver operating characteristic analysis and multivariable logistic regression. Exploratory RF models were constructed to contextualize regression-based findings, with feature importance assessed using permutation importance and the Gini index. These machine learning analyses were conducted as exploratory, hypothesis-generating tools to support and contextualize regression-based findings rather than to establish standalone predictive models. Results: Among 136 patients, 74% had locally advanced disease; pCR was achieved in 52.9%, and radiological response in 84.6%. Higher LMR (≥ 2.98) was independently associated with increased odds of pCR, whereas elevated SII and CAR were associated with reduced response. For radiological response, LMR, CAR, baseline CA 15– 3 levels, and intermediate Ki-67 expression (20– 30%) remained independently associated with outcomes. Exploratory machine-learning analyses consistently identified inflammatory and immune-nutritional biomarkers among the most influential predictors. Conclusion: Routinely available systemic inflammatory and immune-nutritional biomarkers, particularly LMR, SII, and CAR, are independently associated with pathological and radiological response to neoadjuvant dual anti-HER2 therapy in HER2-positive BC. These findings support the potential role of host-related biomarkers in treatment response prediction, pending prospective validation. Plain Language Summary: In patients with HER2-positive breast cancer, predicting response to neoadjuvant therapy remains challenging. This study evaluated whether simple blood-based inflammatory and nutritional biomarkers, including lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII), and C-reactive protein-to-albumin ratio (CAR), are associated with treatment response. The results showed that these routinely available biomarkers were significantly associated with both pathological complete response and radiological response. Because these markers are inexpensive, widely accessible, and easy to calculate, they may provide a practical tool to support treatment decision-making in real-world clinical settings. These findings suggest that incorporating host-related biomarkers alongside standard clinical factors may improve response prediction. However, further prospective and multicenter studies are needed before these biomarkers can be routinely used in clinical practice. Keywords: breast cancer, HER2-positive, neoadjuvant therapy, pathological complete response, inflammation
Şahinli et al. (Wed,) studied this question.