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This prospective investigation identifies neoadjuvant chemotherapy response using PIV in HER2-positive breast cancer, highlighting its potential as a predictive biomarker.
Neoadjuvant chemotherapy (NACT) is the cornerstone in the management of locally advanced breast cancer (LABC), aiming to reduce tumor burden and achieve pathological complete response (pCR), which correlates with improved survival outcomes. Pan-immune-inflammation value (PIV), calculated from peripheral blood counts, reflects systemic inflammation and immune status and has been proposed as prognostic and predictive biomarker in solid tumors. This article evaluates the role of PIV as a predictor marker of response to NACT in locally advanced breast carcinoma and to study the pathological response (residual cancer burden [RCB] score) after NACT in relation to PIV. The current prospective observational investigation was conducted at a tertiary cancer center in Bangalore and included 168 patients with biopsy-proven LABC treated between January 2023 and December 2024. PIV was calculated as (neutrophils × monocytes × platelets)/lymphocytes from pretreatment complete blood counts. All patients received standard anthracycline-taxane–based NACT, with HER2-positive patients receiving trastuzumab. Pathological response was evaluated by employing RCB scoring system. Statistical analysis was done by employing SPSS v30. Among the 168 patients, insignificant associations were observed between PIV status and demographic or baseline clinical characteristics. However, PIV was significantly associated with pathological response. Of the 36 patients who achieved pCR (RCB 0), 88.9% had low PIV and only 11.1% had high PIV (p < 0.001). In contrast, among the 132 nonresponders (RCB 1–3), 78.8% had high PIV. Receiver operating characteristic analysis identified a PIV cutoff of 543.51 with area under the curve of 0.877. This threshold provided sensitivity of 78.8% and a specificity of 88.9% for predicting pCR. Analysis of variance confirmed statistically significant difference in mean PIV between responders and nonresponders (p < 0.001). PIV is a promising, accessible biomarker for predicting response to NACT in LABC. Its use in pretreatment stratification may inform therapeutic decision-making and optimize individualized treatment strategies.
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Nagendrappa et al. (2025) studied this question.
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