Neutrophil-to-Lymphocyte ratio as a prognostic biomarker in extremities undifferentiated pleomorphic sarcoma

Abstract

BackgroundNeutrophil-to-lymphocyte ratio (NLR) in peripheral blood reflects the balance between systemic inflammation and immunity and has been reported as a prognostic biomarker in many neoplastic diseases, but its role in sarcomas has been poorly investigated. In this paper we analyzed the prognostic role of the neutrophil to lymphocyte ratio (NLR) in extremity undifferentiated pleomorphic sarcoma (eUPS). Materials and methodsWe performed an observational, retrospective study including all eUPS cases treated at the National Institute of Cancer in Mexico City from January 2000 to December 2018. We used a ROC analysis to find the cut-off point where the NLR had the best value in predicting death (area under the curve: 0.73, P = 0.001). When the cut-off point was set at 3.09, the sensitivity of the test was 79% and the specificity was 59%. Demographic and clinical variables using log-rank test were also analyzed. Univariate Cox regression analyses and multivariate proportional hazards regression model were carried out to identify independent prognostic factors for Overall survival (OS), Disease-free survival (DFS), Metastasis free survival (MFS) and their association with the NLR. ResultsWe included 112 cases, 53.6% were women. Most cases were stage IIIA (33.9%) or IIIB (30.4%) and Grade 3 (91.1%). High NLR correlated with metastatic disease at presentation (p = 0.001), locally advanced stage (p = 0.05), worse OS (HR = 1.33, 95% CI:1.01-1.75 p = 0.041) and higher risk of specific death (HR = 4.89, 95% CI: 1.88-12.72 p = 0.001). Non-use of chemotherapy (HR: 1.33, 95% CI:1.01-1.75 p = 0.041) was also associated with worse OS. ConclusionThe NLR is a simple yet useful prognostic factor in patients with eUPS when using a cut-off value of 3.09. Soft tissue sarcomas lack routine biomarkers that are applied widely, therefore we propose to consider and include the NLR in prospective trials or prognostic nomograms.