Related Experiment Video
Updated: May 8, 2026
Neutrophil Isolation and Analysis to Determine their Role in Lymphoma Cell Sensitivity to Therapeutic Agents
Published on: March 25, 2016
Dynamic neutrophil-to-lymphocyte ratio predicts prognosis in patients with soft tissue sarcoma: a retrospective study
Yong Jiang1, Yongli Ding1, Weibing Peng1
1Orthopaedic Department, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, Henan, China.
Background:
Soft tissue sarcomas (STS) exhibit significant heterogeneity and are classified as rare tumors with a high risk of metastasis. The neutrophil-to-lymphocyte ratio (NLR), a hematological marker indicative of systemic inflammation, has gained broad recognition for its prognostic utility in oncology. This ratio can be used to evaluate the dynamic changes in inflammatory markers during the diagnosis and treatment of tumors. The value of NLR fluctuations in STS has yet to be fully investigated.
Methods:
This investigation involved a retrospective cohort of 231 patients with STS, all definitively diagnosed and managed at the Musculoskeletal Tumor Center of The First Affiliated Hospital of Zhengzhou University, aiming to evaluate their clinical profiles. The research focused on analyzing the impact of both baseline NLR and its dynamic changes throughout therapy on the prognostic outcomes in STS, with the aim of constructing a nomogram based on delta-NLR.
Results:
The study cohort comprised 231 individuals diagnosed with STS. Based on delta-NLR trends, participants were categorized into two cohorts: an NLR increase group (n=94) and an NLR decrease group (n=137). Analysis using time-dependent receiver operating characteristic (ROC) curves revealed that delta-NLR possessed greater predictive accuracy for prognosis relative to other hematologic parameters and clinical characteristics. Both univariate and multivariate analyses determined that Fédération Nationale des Centres de Lutte Contre le Cancer (FNCLCC) grade, patient age, and delta-NLR served as independent predictors of prognosis. A prognostic nomogram was subsequently constructed integrating these significant factors. The nomogram achieved a C-index of 0.702, and calibration curves verified its accuracy in predicting three- and five-year overall survival (OS) for STS patients. Results from decision curve analysis (DCA) and clinical impact curve assessment additionally validated that utilizing this delta-NLR-based nomogram may offer substantial clinical utility in the management of STS.
Conclusion:
NLR is valuable for continuous monitoring, and ongoing assessment of NLR provides better survival predictions for patients with STS than using baseline NLR alone.