Authors
Guilan Cai, Xiao Zhang, Heyang Zhang, Hanping Shi
Published in
In vivo (Athens, Greece). Volume 40. Issue 5. Pages 3153-3172.
Abstract
Systemic inflammation is increasingly recognized as a key hallmark of cancer progression and an important determinant of patient outcomes, reflecting the balance between tumor-promoting inflammatory activity and anti-tumor immune competence. Using routinely available peripheral blood counts, we evaluated the prognostic value of the neutrophil-to-lymphocyte ratio (NLR) across several common malignancies and developed a pragmatic model for overall survival risk estimation.
From the INSCOC registry, 14,425 patients with lung, gastric, colorectal, liver, brain, or breast cancer were included and randomly split (10,098/4,327) into training and validation sets. Six inflammation-based indices from neutrophil, lymphocyte, and platelet counts were compared for overall survival (OS) using Harrell's C-index and time-dependent receiver operating characteristic (ROC) curves. Associations between NLR and OS were tested by Kaplan-Meier curves, restricted cubic splines, and multivariable Cox models adjusted for demographic, clinical, and treatment factors. A nomogram incorporating NLR and selected routinely available clinical variables was developed and internally evaluated by calibration analysis.
NLR showed the highest, though modest, discrimination across all six cancers (C-index ~0.53-0.63). A threshold of 3.38 identified patients with significantly shorter OS in both sets (log-rank p<0.001). The risk increased progressively with higher NLR and remained significant after multivariable adjustment. Associations were broadly consistent across age, sex, comorbidity, and treatment subgroups. The NLR-based nomogram showed generally acceptable calibration for estimating 1-, 3-, and 5-year survival.
Elevated NLR independently signals worse survival across several major solid tumors and showed higher prognostic discrimination than other evaluated inflammation-derived indices. The proposed nomogram may provide a simple, clinically applicable tool to support individualized risk stratification using routinely available data.
PMID:
42665374
Bibliographic data and abstract were imported from PubMed on 29 Aug 2026.
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