A Novel Nomogram Incorporating the Aggregate Index of Systemic Inflammation, Clinicopathological Parameters and Molecular Classification to Predict Recurrence of Endometrial Cancer: A Multi‐Center Retrospective Study

This study evaluated the aggregate index of systemic inflammation (AISI) for predicting postoperative recurrence in endometrial cancer (EC). A total of 1557 patients were enrolled and divided into training (n = 1030) and validation (n = 527) cohorts. The optimal AISI cutoff was determined by ROC curve analysis. Multivariate Cox regression identified eight independent prognostic factors for recurrence-free survival (all p < 0.05): age ≥ 60 (HR = 1.683, 95% CI 1.191-2.377), FIGO stage III (HR = 2.346, 95% CI 1.480-3.718), LVSI (HR = 1.792, 95% CI 1.226-2.618), CA125 ≥ 35 U/mL (HR = 1.457, 95% CI 1.030-2.062), deep myometrial invasion (HR = 2.021, 95% CI 1.393-2.930), histological type II (HR = 1.798, 95% CI 1.219-2.653), p53 abnormal (HR = 3.252, 95% CI 2.142-4.936), and high AISI (HR = 2.492, 95% CI 1.714-3.625). A prognostic nomogram incorporating these factors was constructed and validated, demonstrating superior predictive accuracy compared to conventional methods. Adjuvant therapy significantly improved outcomes in high-risk patients identified by the nomogram. This comprehensive tool enhances risk stratification and may guide personalized treatment planning.