Nomogram Prediction Model and Prognostic Comparison of Cervical Clear Cell Carcinoma and Cervical Endometrioid Adenocarcinoma: A SEER Database Study
ABSTRACT
Background
Cervical clear cell adenocarcinoma (CCAC) and cervical endometrioid adenocarcinoma (CEAC) are rare and aggressive non‐HPV‐associated malignancies. Despite their histological similarities, these subtypes demonstrate distinct biological behaviors, presenting challenges in treatment and prognosis.
Objective
To develop and validate a multivariable prognostic model for CCAC and CEAC, utilizing the SEER database to enhance clinical decision‐making.
Methods
A total of 775 CEAC and 421 CCAC cases were analyzed using a multivariable nomogram. Patients were randomly allocated to model‐development ( n = 838) and validation ( n = 358) cohorts in a 7:3 ratio. The model's performance was evaluated through AUC, Brier score, and Calibration. Decision Curve Analysis (DCA) and Clinical Impact Curve (CIC) were assessed in both development and internal validation cohorts.
Results
The model exhibited excellent calibration and discrimination in predicting overall survival (OS). In the development cohort, the 12‐ and 24‐month prediction models had AUCs of 0.894 (95% CI: 0.860–0.928) and 0.857 (95% CI: 0.821–0.892), respectively. In the internal validation cohort, the 12‐ and 24‐month models achieved AUCs of 0.814 (95% CI: 0.788–0.840) and 0.798 (95% CI: 0.775–0.822), respectively. The model effectively stratified patients into low‐, intermediate‐, and high‐risk groups, with significantly different median survival times ( p < 0.0001). DCA and CIC further validated the model's clinical utility.
Conclusion
We developed a robust nomogram for quantifying OS risk in CCAC and CEAC patients. This model provides clinicians with a tool for identifying high‐risk patients and implementing timely interventions.