Development and Validation of a Prognostic Nomogram for Endometrial Cancer Based on Systemic Immune-Inflammation Index and Key Clinicopathological Features

Objective: This study aimed to develop and validate a prognostic nomogram integrating systemic immune-inflammatory index (SII) and key clinicopathological features for predicting 2-, 3-, and 5-year overall survival (OS, primary surgery to all-cause death) in patients with Endometrial Cancer (EC), subgrouped into Survivors or Non-survivors, so as to address the unmet need for low-cost, dynamic risk stratification tools in EC precision medicine. Methods: A retrospective cohort of 341 patients with EC (per WHO 2020 criteria) from January 2015 to January 2023 was stratified randomly into training (60%, n=205) and validation (40%, n=136) sets (stratification factors: age). Independent prognostic factors were identified through LASSO and multivariate Cox regression analyses. A nomogram was constructed and evaluated using ROC curves, calibration plots, and decision curve analysis (DCA). Key indicators included pathological differentiation grade, lymphovascular space invasion (LVSI), and systemic immune-inflammatory index (SII). Results: Four independent predictors were identified: age (HR = 1.039, 95% CI: 0.994– 1.086, P = 0.002), pathological differentiation grade (HR = 0.384, 95% CI: 0.188– 0.786, P = 0.001), LVSI (HR = 4.208, 95% CI: 1.523– 11.625, P = 0.001), and SII (HR = 1.001, 95% CI: 1.001– 1.002, P < 0.001). The nomogram demonstrated excellent discrimination, with AUCs of 0.881, 0.883, and 0.874 for 2-, 3-, and 5-year OS in the training cohort, and 0.870, 0.834, and 0.838 in the validation cohort. Conclusion: This study successfully developed and validated a prognostic model for EC based on SII and pathological differentiation. The model significantly outperformed traditional clinical parameters and may serve as a valuable tool for early risk stratification and individualized management in clinical practice. Keywords: endometrial cancer, prognosis, nomogram, systemic immune-inflammation index, overall survival, predictive model