A novel systemic inflammatory-nutritional score (INS) and nomogram for the prognostic prediction of adult head and neck soft tissue sarcoma in patients undergoing R0 surgery

Abstract

Abstract Background Head and neck soft tissue sarcoma (HNSTS) comprises a rare group of malignancies with high risks of recurrence and mortality. However, the biomarkers predicting the prognosis of HNSTS patients received R0 resection are limited. Here, we aimed to develop a novel inflammatory-nutritional score (INS) system and a nomogram to explore the prognostic value of preoperative biomarkers in HNSTS patients. Methods With a median follow-up time of 134.6 months, 315 patients with HNSTS who underwent R0 resection were enrolled. Clinical characteristics and hematological features were collected. The least absolute shrinkage and selection operator Cox regression model was used to select the most significant survival‑associated candidate for constructing the INS. The relationship between the INS groups and clinical features was analyzed. Further, a nomogram based on the INS and clinical features was generated by multivariate Cox analysis, assessed by the concordance index and internally validated by bootstraps. Results The five-year overall survival (OS) rate, three-year recurrence-free survival rate and disease-free survival (DFS) rate were 77.3%, 61.0% and 55.4%, respectively. After scoring, the novel INS system was established and divided into 3 groups: Low Risk (INS 0), Medium Risk (INS 1–3) and High Risk (INS 4–7). High INSs were associated with a deep tumor location (p < 0.001), high tumor grade (p < 0.001), and advanced American Joint Committee on Cancer stage (p < 0.001). The Low-Risk group exhibited a higher 5-year OS rate and 3-year DFS rate than the Medium-Risk and High-Risk groups (87.6% versus 81.3%% versus 53.3%, p < 0.001; 62.2% versus 56.9% versus 37.9%, p = 0.007). Moreover, the multivariate analysis demonstrated that the INS (p = 0.023), tumor depth (p < 0.001), pT stage (p = 0.022), pN stage (p < 0.001) and tumor grade (p < 0.001) were independent survival predictors for HNSTS patients. Based on these results, a novel prognostic nomogram for OS was generated, which showed a better performance than the p7TNMG stage alone (p < 0.001). Conclusions Our findings suggest that oncological outcomes among HNSTS patients who underwent R0 resection can be accurately predicted using the INS, therefore, an INS-based specific nomogram provides reliable, individualized prognostic information for patients with HNSTS to guide treatment strategies in clinical practice.