Application of a Nomogram Integrating Ultrasound Data With Clinical Characteristics to Differentiate Between Uterine Sarcoma and Uterine Fibroids

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Authors: Chunzhen Huang, Yujuan Weng, Baiwei Lin
Cited by: 2
References: 26

Abstract

Background: To assess the diagnostic value of a nomogram that integrates ultrasound and clinical features to differentiate uterine sarcoma from uterine fibroids. Methods: In this retrospective analysis, data from 60 uterine sarcoma patients and 60 uterine fibroid patients confirmed by surgical pathology at the Affiliated Hospital of Putian University (August 2024–June 2025) were examined. Clinical variables (age, disease duration, menopausal status, postmenopausal bleeding), laboratory markers (carbohydrate antigen 125 [CA125], lactate dehydrogenase [LDH]), and ultrasound characteristics (maximal diameter, margin, echogenicity, cystic change, calcification, and Adler blood flow grading) were collected. Independent predictors were determined through both univariate and multivariate logistic regression analyses. Predictive models were constructed and evaluated via receiver operating characteristic (ROC) curves, with model robustness further assessed through tenfold cross-validation and bootstrap validation. Results: The groups were successfully matched for key baseline characteristics (age, disease duration, menopausal status; all p > 0.05). Multivariate analysis revealed that age, postmenopausal bleeding, LDH, CA125, echogenicity, and tumor margin were independent predictors. The combined model demonstrated enhanced diagnostic ability with an area under the curve (AUC) of 0.902 (95% CI: 0.847–0.935), outperforming individual models based on clinical (AUC: 0.764), laboratory (AUC: 0.651), and ultrasound (AUC: 0.804) data. The model’s generalizability was confirmed by internal validation, showing strong maintained performance (tenfold cross-validated AUC: 0.885; bootstrap-corrected AUC: 0.887). Conclusion: A nomogram based on combined clinical, laboratory, and ultrasound features provides high accuracy for differentiating uterine sarcoma from fibroids, supporting clinical decision-making.

Fields of Study & Subjects

Uterine Myomas and Treatments Endometrial and Cervical Cancer Treatments Maternal and fetal healthcare

Publication details

Journal / source
Clinical and Experimental Obstetrics & Gynecology
Publisher
IMR Press
Volume
53
Issue
3
Publication date
16 March 2026
Language
EN