Constructing a Nomogram for Predicting Pelvic Osteosarcoma: A Retrospective Study Based on the SEER Database and a Chinese Cohort

<b>Aims/Background</b> Generally, pelvic osteosarcoma has a worse prognosis compared with limb osteosarcoma. This study aims to create and validate a new nomogram for predicting the prognosis of pelvic osteosarcoma. <b>Methods</b> Clinical data of 62 patients derived from the Surveillance, Epidemiology, and End Results (SEER) database and 31 Chinese patients diagnosed with pelvic osteosarcoma were gathered. Kaplan-Meier survival analysis was utilized to calculate the median survival time for all variables. Univariate and multivariate Cox regression models were employed to identify the prognostic factors of pelvic osteosarcoma. A nomogram was constructed using data gleaned from the SEER cohort and verified using the receiver operating characteristic (ROC) curve and calibration plot in the Chinese cohort. <b>Results</b> Kaplan-Meier analysis revealed that individuals of other races (Asians) (hazard ratio (HR) = 0.24, 95% confidence interval (CI): 0.1-0.57, <i>p</i> = 0.001), aged ≤51 years old (HR = 0.4, 95% CI: 0.22-0.73, <i>p</i> = 0.003), and with tumor size ≤160 mm (HR = 0.37, 95% CI: 0.2-0.71, <i>p</i> = 0.03) had better survival outcomes. Conversely, factors such as no primary surgery (HR = 3.6, 95% CI: 1.81-7.15, <i>p</i> < 0.001), lung metastasis (HR = 1.96, 95% CI: 1.17-3.28, <i>p</i> = 0.010), and radiotherapy (HR = 1.89, 95% CI: 1.10-3.25, <i>p</i> = 0.021) were associated with poorer survival. Multivariate Cox analysis indicated that lung metastasis (HR = 2.57, 95% CI: 1.29-5.13, <i>p</i> = 0.008), other races (Asians) (HR = 0.23, 95% CI: 0.07-0.75, <i>p</i> = 0.015), tumor size (HR = 0.28, 95% CI: 0.13-0.62, <i>p</i> = 0.001) and age (HR = 0.3, 95% CI: 0.16-0.59, <i>p</i> < 0.001) were independent prognostic factors for pelvic osteosarcoma. Univariate and multivariate Cox regression models identified three independent variables in the training cohort: age, lung metastasis, and tumor size. A predictive nomogram was developed based on the data from the SEER cohort and validated in the Chinese cohort. The areas under the curves (AUCs) that are used to predict 1-year, 2-year, and 3-year survival rates were 0.81 (95% CI: 0.68-0.94), 0.75 (95% CI: 0.63-0.86), and 0.80 (95% CI: 0.70-0.89) in the training cohort, and 0.67 (95% CI: 0.30-1.04), 0.66 (95% CI: 0.43-0.90) and 0.71 (95% CI: 0.50-0.93) in the validation cohort. <b>Conclusion</b> The predictive nomogram constructed in this study facilitates accurate and effective prediction of the overall survival of patients with pelvic osteosarcoma and helps enhance the clinical decision-making process.