Evidence map›Paper›PMID 42597227›Full record

ArticleAmerican journal of cancer research2026

Integration of serological markers with O-RADS ultrasound risk stratification achieves high diagnostic accuracy for early ovarian cancer: development and validation of an interpretable model.

Tingting Hua, Xinchun Wu, Weihui Liu, Zhiying Jia, Lianhua Zhang, Dilibaier Abuduniyazi, Yan Ma, Li Li, Xiaoyan Zhu, Muzaipaer Muhetaer and 2 more

Abstract read
In one paragraph

Article in American journal of cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Tingting HuaDepartment of Ultrasound Diagnosis, The 3rd Affiliated Teaching Hospital of Xinjiang Medical University (Affiliated Cancer Hospital) Urumqi 830010, Xinjiang Uygur Autonomous Region, China.
Xinchun WuMedical Imaging Center, The Fifth Affiliated Hospital of Xinjiang Medical University Urumqi 830026, Xinjiang Uygur Autonomous Region, China.
Weihui LiuDepartment of Ultrasound, Midong District Traditional Chinese Medicine Hospital Urumqi 831400, Xinjiang Uygur Autonomous Region, China.
Zhiying JiaDepartment of Ultrasound Diagnosis, The 3rd Affiliated Teaching Hospital of Xinjiang Medical University (Affiliated Cancer Hospital) Urumqi 830010, Xinjiang Uygur Autonomous Region, China.
Lianhua ZhangDepartment of Ultrasound Diagnosis, The 3rd Affiliated Teaching Hospital of Xinjiang Medical University (Affiliated Cancer Hospital) Urumqi 830010, Xinjiang Uygur Autonomous Region, China.
Dilibaier AbuduniyaziDepartment of Ultrasound, Xinjiang Uygur Medicine Hospital (Second People's Hospital of Xinjiang Uygur Autonomous Region) Urumqi 830001, Xinjiang Uygur Autonomous Region, China.
Yan MaDepartment of Ultrasound Diagnosis, The 3rd Affiliated Teaching Hospital of Xinjiang Medical University (Affiliated Cancer Hospital) Urumqi 830010, Xinjiang Uygur Autonomous Region, China.
Li LiDepartment of Ultrasound Diagnosis, The 3rd Affiliated Teaching Hospital of Xinjiang Medical University (Affiliated Cancer Hospital) Urumqi 830010, Xinjiang Uygur Autonomous Region, China.
Xiaoyan ZhuDepartment of Ultrasound, Shule County People's Hospital Kashgar Prefecture 844000, Xinjiang Uygur Autonomous Region, China.
Muzaipaer MuhetaerDepartment of Ultrasound, Shule County People's Hospital Kashgar Prefecture 844000, Xinjiang Uygur Autonomous Region, China.
Abudushalamu AbulaitiDepartment of Ultrasound, Shule County People's Hospital Kashgar Prefecture 844000, Xinjiang Uygur Autonomous Region, China.
Fucheng MaDepartment of Ultrasound Diagnosis, The 3rd Affiliated Teaching Hospital of Xinjiang Medical University (Affiliated Cancer Hospital) Urumqi 830010, Xinjiang Uygur Autonomous Region, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to enhance preoperative diagnostic accuracy for early ovarian cancer (EOC) by constructing and validating an interpretable predictive model integrating serological markers with O-RADS ultrasound risk stratification. A total of 674 patients with adnexal masses (270 EOC, 404 benign) were enrolled and randomly assigned to training (n=438) and validation (n=236) sets. Multivariate logistic regression identified cancer antigen 125 (CA125; P=0.002), human epididymal protein 4 (HE4; P=0.001), carcinoembryonic antigen (CEA; P=0.005), maximum tumor diameter (P=0.005), and Ovarian-Adnexal Reporting and Data System (O-RADS) classification (P<0.001) as independent predictors. Among individual indices, O-RADS performed best (AUC=0.854), followed by CA125 (AUC=0.783), HE4 (AUC=0.744), CEA (AUC=0.717), and maximum tumor diameter (MTD; AUC=0.696). The comprehensive model achieved an AUC of 0.969 (95% CI: 0.953-0.985) in the training set and 0.973 (95% CI: 0.952-0.994) in the validation set, with sensitivity of 0.907/0.897, specificity of 0.914/0.980, and accuracy of 0.911/0.949, significantly outperforming both the marker combination model (AUC=0.918) and individual indices (DeLong test, all P<0.05). Robust calibration was confirmed (training set: Brier score=0.062, Hosmer-Lemeshow P=0.126; validation set: Brier score=0.056, Hosmer-Lemeshow P=0.578), and decision curve analysis demonstrated positive net benefits across a wide threshold probability range. SHAP analysis identified O-RADS classification, CA125, and HE4 as the most influential predictors, with notable interactions among them. Bootstrap resampling and 5-fold cross-validation confirmed model stability. The comprehensive model demonstrated excellent diagnostic performance, robust calibration, and clinical utility, providing a reliable interpretable tool for preoperative EOC risk stratification.

Indexed as

CA125Early ovarian cancerHE4logistic regressionO-RADSpredictive modelsSHAP

Identifiers

PMID42597227
PMCPMC13468248

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.