ArticleBiomolecules & biomedicine2026
Breast cancer response to neoadjuvant chemotherapy: Pre-treatment NLR, PLR, LMR, and SII do not predict pathological complete response or residual cancer burden.
Article in Biomolecules & biomedicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
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6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Inflammation-based indices, derived from routine complete blood count parameters such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune-inflammation index (SII), have garnered considerable attention as potential prognostic markers for treatment response in breast cancer. Nevertheless, their predictive utility in patients undergoing neoadjuvant chemotherapy (NACT) remains equivocal. This study aimed to investigate the association between pre-treatment inflammatory indices and pathological complete response (pCR) and residual cancer burden (RCB) in breast cancer patients receiving NACT. A retrospective analysis was conducted on 110 consecutive patients with invasive breast carcinoma who received NACT followed by curative surgery at a single institution. Pre-treatment values for NLR, PLR, LMR, and SII were calculated from routine laboratory data. Given the non-normal distribution of inflammatory indices, as determined by Shapiro-Wilk testing, non-parametric analyses were employed. Group comparisons utilized the Mann-Whitney U and Kruskal-Wallis tests. Predictive performance was assessed using receiver operating characteristic (ROC) analysis with 500-iteration bootstrap resampling. Multivariable logistic regression was applied to identify independent predictors of pCR. The findings revealed no significant associations between any of the inflammatory indices and pCR or RCB class distribution. ROC analyses indicated poor discriminatory performance for all indices, with area under the curve (AUC) values consistently approximating 0.50. In the multivariable analysis, only Ki-67 ≥14% independently predicted pCR (OR 7.077, 95% CI 2.210-22.662; p=0.001). In conclusion, pre-treatment NLR, PLR, LMR, and SII did not exhibit clinically meaningful predictive value for pathological response to NACT within this cohort. Tumor proliferative activity, as reflected by Ki-67, remained the most robust independent predictor of treatment response.
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