Use of Nomogram on Nutritional Assessment Indicators to Predict Clinical Outcomes in Patients Undergoing Surgical Resection for High-Grade Osteosarcoma

To evaluate the prognostic values of nutrition-associated indicators and develop nutritional models for prediction of different clinical outcomes in patients with high-grade osteosarcoma receiving surgical resection. Patients diagnosed as high-grade osteosarcomas were included between 2008 and 2018. Body mass index (BMI), Glasgow prognostic score (GPS), systematic inflammatory index (SII), and controlling nutritional score (CONUT) were calculated as nutrition-associated indicators. The primary outcome was overall survival (OS) as the long-term outcome, and the secondary outcome was the postoperative hospitalization duration as the short-term outcome. The prognostic values of nutrition-associated indicators were evaluated by univariate and multivariate analyses to recognize the potential predictors for construction of nomogram model with validation. High GPS and CONUT yielded poor OS independently [GPS: HR (95% CI): 3.262 (2.035-5.229), p < 0.001; CONUT: HR (95% CI): 2.445 (1.508-3.964), p < 0.001]. The nomogram model for OS showed great prediction abilities and moderate calibration performance after integrating GPS and CONUT. CONUT was also identified as the independent predictor for hospitalization duration [OR (95% CI): 1.950 (1.145-3.321), p = 0.014]. The CONUT score was considered as the significant predictor in prediction of OS and hospitalization duration. Appropriate management for nutritional status might optimize patients' prognoses with reference to nutrition-associated indicators.