Clinical significance of peripheral blood parameters as a prognostic biomarker in patients receiving neoadjuvant chemotherapy for breast cancer

Systemic inflammatory responses play a crucial role in cancer progression, and peripheral blood biomarkers have emerged as potential prognostic and predictive markers in various malignancies. This study evaluated the efficacy of serial peripheral blood biomarkers as independent prognostic and predictive indicators in patients with breast cancer who received neoadjuvant chemotherapy. This retrospective cohort study investigated the prognostic value of peripheral blood biomarkers, including red cell distribution width (RDW), RDW to platelet count ratio (RPR), platelet count (PLT), platelet distribution width (PDW), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), PDW to platelet count ratio (PDW/P), and mean platelet volume (MPV) in patients with breast cancer treated with neoadjuvant chemotherapy at a single institution, from 2007 to 2013. Blood samples were collected at diagnosis, after neoadjuvant chemotherapy, after surgery, and 6–12 months postoperatively. Statistical analyses included t-tests, chi-square tests, Cox regression for survival, and logistic regression for clinical responses to neoadjuvant chemotherapy. Longitudinal changes in biomarkers were analyzed using linear mixed-effects models. Among 1,139 patients receiving neoadjuvant chemotherapy, 15.2% achieved pathological complete response (pCR). Tumor size, histologic grade, and molecular subtype were independent predictors of pCR, whereas baseline hematologic biomarkers did not predict pCR. At diagnosis, elevated PDW, NLR, and MPV were associated with worse disease-free survival (DFS) and breast cancer-specific survival (BCSS) in multivariate analysis. During follow-up, elevated RDW, RPR, PDW, PDW/P, NLR, and MPV remained significant predictors of poor prognosis. NLR consistently predicted worse DFS and BCSS (HRs, 1.06; p < 0.001). Time-sequence analysis showed significant changes in NLR, PDW, and MPV over time (all p < 0.001), with persistently higher NLR in the recurrence group (interaction p = 0.0003). Although baseline hematologic biomarkers did not predict pCR, several biomarkers such as NLR, PDW, and MPV demonstrated strong prognostic value for long-term survival. Notably, NLR also showed prognostic relevance through longitudinal changes, supporting its potential role as a dynamic biomarker.

Authors

Institutions

Publication Details

Journal
BMC Cancer
Published
2026-01-03
DOI
https://doi.org/10.1186/s12885-025-15510-0
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Clinical significance of peripheral blood parameters as a prognostic biomarker in patients receiving neoadjuvant chemotherapy for breast cancer

Tae-In Yoon, H Kim, Ji Hyeon Lee, Byung Ho Son et al.
BMC Cancer
Inflammatory Biomarkers in Disease Prognosis
article

Clinical significance of peripheral blood parameters as a prognostic biomarker in patients receiving neoadjuvant chemotherapy for breast cancer

Tae-In Yoon, H Kim, Ji Hyeon Lee, Byung Ho Son, Sae Byul Lee, Seunghee Baek, Tae Kyung Yoo, Jisun Kim, Il Yong Chung, Jong Won Lee, Beom Seok Ko
article en

Abstract

Systemic inflammatory responses play a crucial role in cancer progression, and peripheral blood biomarkers have emerged as potential prognostic and predictive markers in various malignancies. This study evaluated the efficacy of serial peripheral blood biomarkers as independent prognostic and predictive indicators in patients with breast cancer who received neoadjuvant chemotherapy. This retrospective cohort study investigated the prognostic value of peripheral blood biomarkers, including red cell distribution width (RDW), RDW to platelet count ratio (RPR), platelet count (PLT), platelet distribution width (PDW), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), PDW to platelet count ratio (PDW/P), and mean platelet volume (MPV) in patients with breast cancer treated with neoadjuvant chemotherapy at a single institution, from 2007 to 2013. Blood samples were collected at diagnosis, after neoadjuvant chemotherapy, after surgery, and 6–12 months postoperatively. Statistical analyses included t-tests, chi-square tests, Cox regression for survival, and logistic regression for clinical responses to neoadjuvant chemotherapy. Longitudinal changes in biomarkers were analyzed using linear mixed-effects models. Among 1,139 patients receiving neoadjuvant chemotherapy, 15.2% achieved pathological complete response (pCR). Tumor size, histologic grade, and molecular subtype were independent predictors of pCR, whereas baseline hematologic biomarkers did not predict pCR. At diagnosis, elevated PDW, NLR, and MPV were associated with worse disease-free survival (DFS) and breast cancer-specific survival (BCSS) in multivariate analysis. During follow-up, elevated RDW, RPR, PDW, PDW/P, NLR, and MPV remained significant predictors of poor prognosis. NLR consistently predicted worse DFS and BCSS (HRs, 1.06; p < 0.001). Time-sequence analysis showed significant changes in NLR, PDW, and MPV over time (all p < 0.001), with persistently higher NLR in the recurrence group (interaction p = 0.0003). Although baseline hematologic biomarkers did not predict pCR, several biomarkers such as NLR, PDW, and MPV demonstrated strong prognostic value for long-term survival. Notably, NLR also showed prognostic relevance through longitudinal changes, supporting its potential role as a dynamic biomarker.

BMC CancerVol. 26(1)
Ulsan College (KR), University of Ulsan (KR), Dongnam Institute of Radiological & Medical Sciences (KR)
Good health and well-being
Openalex Percentile: Top 99%
Inflammatory Biomarkers in Disease Prognosis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.