Increasing evidence indicates the involvement of inflammation and coagulation in cancer progression and metastases. Inflammatory biomarkers hold great promise for improving the predictive ability of existing prognostic tools in cancer patients. In the present study, we investigated several inflammatory indices with regard to their prognostic relevance for predicting clinical outcome in soft tissue sarcoma (STS) patients. Three hundred and forty STS patients were divided into a training set (n 5 170) and a validation set (n 5 170). Besides well-established clinico-pathological prognostic factors, we evaluated the prognostic value of the neutrophil/lymphocyte (N/L) ratio, the lymphocyte/monocyte (L/M) ratio and the platelet/lymphocyte (P/L) ratio using Kaplan-Meier curves and univariate as well as multivariate Cox regression models. Additionally, we developed a nomogram by supplementing the L/M ratio to the well-established Kattan nomogram and evaluated the predictive accuracy of this novel nomogram by applying calibration and Harrell's concordance index (c-index). In multivariate analysis, a low L/M ratio was significantly associated with decreased CSS and DFS (HR 5 0.41, 95% CI 5 0.18-0.97, p 5 0.043; HR 5 0.39, 95% CI 5 0.16-0.91, p 5 0.031, respectively) in the training set. Using the validation set for confirmation, we found also in multivariate analysis an independent value for CSS (HR 5 0.33, 95% CI 5 0.12-0.90, p 5 0.03) and for DFS (HR 5 0.36, 95% CI 5 0.16-0.79, p 5 0.01). The estimated c-index was 0.74 using the original Kattan nomogram and 0.78 when the L/M ratio was added. Our study reports for the first time that the pre-operative L/M ratio represents a novel independent prognostic factor for prediction the clinical outcome in STS patients. This easily determinable biomarker might be helpful in improved individual risk assessment.Soft tissue sarcomas (STS) account for nearly 11,280 cases per year and are responsible for about 3,900 deaths in the United States annually, mainly due to local recurrence or metastatic disease. 1 Therefore, it is crucial to understand the biological mechanisms that contribute to tumor progression and to identify novel prognostic markers to generate individualized treatment and follow-up schedules. In a large retrospective study of 2,136 STS patients, Kattan et al. developed a postoperative prognostic model that predicts sarcomaspecific death, based on traditional prognostic factors such as age at diagnosis, tumor size, histologic grade, histologic subtype, tumor depth and site. 2 This nomogram is useful for general risk assessment and has potential value in determining surgical strategy and adjuvant management. Nevertheless, novel prognostic factors might be helpful in improving its predictive ability. Current approaches in cancer research have focused on the characterization of novel biomarkers, which ideally should be easily accessible, highly reproducible, cheap and most importantly, identify patients at high risk for disease-recurrence and death. Increasing evidence su...