Development and validation of a prognostic nomogram for ovarian clear cell carcinoma: a study based on the SEER database and a Chinese cohort
Abstract Background The clinical prognostic factors for ovarian clear cell carcinoma (OCCC) are limited, and we aim to construct a model to predict the survival of OCCC patients. Methods Data were extracted from the SEER database for patients diagnosed with OCCC. Cox regression analyses were used to...
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| Format: | Article |
| Language: | English |
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Springer
2025-04-01
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| Series: | Discover Oncology |
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| Online Access: | https://doi.org/10.1007/s12672-025-02272-1 |
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| author | Yao Shen Fei Xi Pingge Zhao Yuhang Zhang Guanlin Guo Xueyuan Jia Jie Wu Ye Kuang |
| author_facet | Yao Shen Fei Xi Pingge Zhao Yuhang Zhang Guanlin Guo Xueyuan Jia Jie Wu Ye Kuang |
| author_sort | Yao Shen |
| collection | DOAJ |
| description | Abstract Background The clinical prognostic factors for ovarian clear cell carcinoma (OCCC) are limited, and we aim to construct a model to predict the survival of OCCC patients. Methods Data were extracted from the SEER database for patients diagnosed with OCCC. Cox regression analyses were used to identify independent risk factors for OCCC. Two nomograms were developed, and the results were evaluated comprehensively by C-index, ROC curve, calibration curve, and DCA curve. Patients diagnosed with OCCC were used as the validation set to verify the model. Results A total of 1855 OCCC patients from the SEER database were used as the training set, and 101 patients from our hospital were used as the validation set. Cox regression analysis of the independent risk factors affecting the prognosis of OCCC was used to construct nomograms. The C-index of the training set OS was 0.76, and the validation set OS was 0.75. The AUC of the training set OS is 0.803, 0.794, and 0.802 for 1, 3, and 5 years, and 0.774, 0.800, and 0.923 for the validation set. The calibration curve and DCA curve also showed that OS and CSS have good predictive power. Conclusions A nomogram based on 8 prognostic factors analyzed by Cox regression can predict the prognosis of OCCC patients effectively. |
| format | Article |
| id | doaj-art-d88d5746c7024145b07603095e6cab38 |
| institution | OA Journals |
| issn | 2730-6011 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Oncology |
| spelling | doaj-art-d88d5746c7024145b07603095e6cab382025-08-20T02:17:10ZengSpringerDiscover Oncology2730-60112025-04-0116111210.1007/s12672-025-02272-1Development and validation of a prognostic nomogram for ovarian clear cell carcinoma: a study based on the SEER database and a Chinese cohortYao Shen0Fei Xi1Pingge Zhao2Yuhang Zhang3Guanlin Guo4Xueyuan Jia5Jie Wu6Ye Kuang7Laboratory of Medical Genetics, Harbin Medical UniversityLaboratory of Medical Genetics, Harbin Medical UniversityDepartment of Gynecology and Obstetrics, The 2nd Affiliated Hospital of Harbin Medical UniversityDepartment of Gynecology and Obstetrics, The 2nd Affiliated Hospital of Harbin Medical UniversityLaboratory of Medical Genetics, Harbin Medical UniversityLaboratory of Medical Genetics, Harbin Medical UniversityLaboratory of Medical Genetics, Harbin Medical UniversityDepartment of Gynecology and Obstetrics, The 2nd Affiliated Hospital of Harbin Medical UniversityAbstract Background The clinical prognostic factors for ovarian clear cell carcinoma (OCCC) are limited, and we aim to construct a model to predict the survival of OCCC patients. Methods Data were extracted from the SEER database for patients diagnosed with OCCC. Cox regression analyses were used to identify independent risk factors for OCCC. Two nomograms were developed, and the results were evaluated comprehensively by C-index, ROC curve, calibration curve, and DCA curve. Patients diagnosed with OCCC were used as the validation set to verify the model. Results A total of 1855 OCCC patients from the SEER database were used as the training set, and 101 patients from our hospital were used as the validation set. Cox regression analysis of the independent risk factors affecting the prognosis of OCCC was used to construct nomograms. The C-index of the training set OS was 0.76, and the validation set OS was 0.75. The AUC of the training set OS is 0.803, 0.794, and 0.802 for 1, 3, and 5 years, and 0.774, 0.800, and 0.923 for the validation set. The calibration curve and DCA curve also showed that OS and CSS have good predictive power. Conclusions A nomogram based on 8 prognostic factors analyzed by Cox regression can predict the prognosis of OCCC patients effectively.https://doi.org/10.1007/s12672-025-02272-1Ovarian clear cell carcinomaOverall survivalCancer-specific survivalSEER databaseNomogram |
| spellingShingle | Yao Shen Fei Xi Pingge Zhao Yuhang Zhang Guanlin Guo Xueyuan Jia Jie Wu Ye Kuang Development and validation of a prognostic nomogram for ovarian clear cell carcinoma: a study based on the SEER database and a Chinese cohort Discover Oncology Ovarian clear cell carcinoma Overall survival Cancer-specific survival SEER database Nomogram |
| title | Development and validation of a prognostic nomogram for ovarian clear cell carcinoma: a study based on the SEER database and a Chinese cohort |
| title_full | Development and validation of a prognostic nomogram for ovarian clear cell carcinoma: a study based on the SEER database and a Chinese cohort |
| title_fullStr | Development and validation of a prognostic nomogram for ovarian clear cell carcinoma: a study based on the SEER database and a Chinese cohort |
| title_full_unstemmed | Development and validation of a prognostic nomogram for ovarian clear cell carcinoma: a study based on the SEER database and a Chinese cohort |
| title_short | Development and validation of a prognostic nomogram for ovarian clear cell carcinoma: a study based on the SEER database and a Chinese cohort |
| title_sort | development and validation of a prognostic nomogram for ovarian clear cell carcinoma a study based on the seer database and a chinese cohort |
| topic | Ovarian clear cell carcinoma Overall survival Cancer-specific survival SEER database Nomogram |
| url | https://doi.org/10.1007/s12672-025-02272-1 |
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