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April 27, 2026Cancer Medicine0 citationsOpen Access

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

CTChenfan TianThe Affiliated Yongchuan Hospital of Chongqing Medical University NZNa ZengWannan Medical College YTYuan TuThe Affiliated Yongchuan Hospital of Chongqing Medical University

Key Points

The aim is to evaluate the aggregate index of systemic inflammation (AISI) for predicting postoperative recurrence in endometrial cancer.
Evaluated 1557 patients, divided into training (n=1030) and validation (n=527) cohorts.
Used ROC curve analysis to determine optimal AISI cutoff.
Developed a prognostic nomogram based on multivariate Cox regression identifying eight prognostic factors.
Identified eight independent factors associated with recurrence-free survival, including age ≥ 60 (HR = 1.683), FIGO stage III (HR = 2.346), and high AISI (HR = 2.492).
The nomogram demonstrated superior predictive accuracy compared to conventional methods.
Adjuvant therapy significantly improved outcomes for high-risk patients identified by the nomogram.

Abstract

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.

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