Work

Pan-cancer Evaluation of the Neutrophil-to-Lymphocyte Ratio as a Prognostic Marker Across Six Major Solid Tumors

Year: 2026

Type: article

Abstract: BACKGROUND/AIM: 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. PATIENTS AND METHODS: 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. RESULTS: <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. CONCLUSION: 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.

Source: In Vivo

DOI: 10.21873/invivo.14413

Authors: GUILAN CAI, XIAO ZHANG, HEYANG ZHANG, HANPING SHI

Institutions: Capital Medical University, Beijing Friendship Hospital, First Affiliated Hospital of Wenzhou Medical University

Language: English

Topic: Inflammatory Biomarkers in Disease Prognosis

Subfield: Oncology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W7204577881