ArticleBMC cancer2026
Integration of Ki67 and Pan-Immune-Inflammation Value (PIV) into a predictive nomogram for pathologic complete response in triple-negative breast cancer : (Ki67 and inflammation in triple-negative breast cancer).
Article in BMC cancer, 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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1 citing paper in PubMed.
- Dynamic Assessment of Systemic Inflammatory Markers in Predicting Pathological Complete Response After Neoadjuvant Treatment in Triple-Negative Breast Cancer.Journal of clinical medicine · 2026Article
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10 authors.
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Abstract
backgroundTriple-negative breast cancer (TNBC) shows substantial heterogeneity in response to neoadjuvant therapy (NAT). Simple, reproducible biomarkers that help identify patients more likely to achieve pathologic complete response (pCR) are needed.
methodsThis multicenter retrospective cohort included 137 patients with TNBC treated with anthracycline–taxane–based NAT between 2015 and 2023, with or without carboplatin. The Ki67 proliferation index and pan-immune-inflammation value (PIV = neutrophil × monocyte × platelet / lymphocyte) were evaluated for their association with pCR Receiver operating characteristic (ROC) analyses identified optimal cut-offs (Ki67: 27.5%; PIV: 292). Patients were categorized into four Ki67–PIV subgroups. Multivariable logistic regression was used to examine associations with pCR, and a nomogram was developed incorporating tumor size, clinical nodal status, chemotherapy regimen, and Ki67–PIV subgroup. Discrimination, calibration, and internal validation were assessed using ROC AUC, calibration plots, and bootstrap resampling (B = 1000).
resultsThe overall pCR rate was 41% (56/137). pCR rates differed across Ki67–PIV subgroups (p < 0.001), with the High Ki67–Low PIV subgroup showing the highest pCR proportion (84%; 31/37) and the lowest proportions observed in Low Ki67–High PIV (12%; 4/34) and Low Ki67–Low PIV (11%; 1/9) subgroups. In multivariable analysis, the High Ki67–Low PIV phenotype was independently associated with pCR (OR 1.88, 95% CI 1.34–2.97; p < 0.001), and carboplatin-containing NAT was also independently associated with higher pCR likelihood (OR 1.75, 95% CI 1.12–2.64; p < 0.001). The nomogram demonstrated strong discrimination (AUC = 0.86), with a bootstrap-corrected AUC of 0.84 and good calibration.
conclusionIn this retrospective multicenter cohort, integrating Ki67 and PIV enabled biomarker-defined stratification of pCR after NAT in TNBC. A nomogram incorporating clinical variables, regimen, and the Ki67–PIV phenotype may provide a pragmatic approach for risk stratification, although external validation is required before broader clinical application.
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