Development and Validation of a Prognostic Nomogram for Endometrial Cancer Based on Systemic Immune-Inflammation
Jialu Lu1,2, Ziyi Lin1,2, Yu Tian3
1The First Clinical Medical College, Guangdong Medical University, Zhanjiang, Guangdong, People's Republic of China.
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.
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