Prognosis risk stratification in patients with cervical adenocarcinoma after surgery: Development and validation of integrated biomarkers

L Jian ¹, N Wu ², F Bi ¹

⁰Department of Radiology, Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, Hunan, China.

Clinical Radiology +

|

August 6, 2025

View abstract on PubMed

Summary

A new prognostic tool integrates imaging, clinical, and DNA methylation data to predict outcomes for cervical adenocarcinoma (CAC) patients. This combined model improves risk stratification, aiding disease monitoring and treatment decisions.

Area Of Science

Oncology
Radiology
Genomics

Background

Cervical adenocarcinoma (CAC) currently lacks validated prognostic assessment tools.
Accurate prognosis is crucial for effective disease monitoring and clinical decision-making in CAC patients.

Purpose Of The Study

To develop and validate a novel prognostic tool for surgically treated cervical adenocarcinoma (CAC) patients.
To integrate radiomic features from contrast-enhanced computed tomography (CECT) images, clinicopathologic variables, and DNA methylation data for enhanced prognostic accuracy.

Main Methods

Retrospective collection of clinical and imaging data from 127 CAC patients (86 training, 41 validation).
Construction of pre-contrast, post-contrast, and fusion radiomic models using support-vector-machine classification.
Development of a combined prognostic model integrating clinical, radiomic, and DNA methylation data (ZNF582) for progression-free survival (PFS) prediction.

Main Results

The combined model, incorporating chemoradiotherapy, ZNF582 methylation, and post-contrast radiomic features, achieved the highest concordance index (C-index) of 0.872 in the validation cohort.
The clinical model (chemoradiotherapy, invasion depth) showed a C-index of 0.811, while radiomic models ranged from 0.723 to 0.757.
Kaplan-Meier analysis confirmed significantly shorter PFS for high-risk patients stratified by the models (all P<0.05).

Conclusions

The developed combined prognostic model demonstrates robust performance for risk stratification in cervical adenocarcinoma (CAC) patients.
This integrated tool can significantly aid in disease monitoring and inform clinical decision-making for improved patient management.

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