Nomogram prediction of overall survival in breast cancer patients post-surgery: integrating SEER database and multi-center evidence from China
PurposeOverall survival (OS) in postoperative breast cancer patients is influenced by various clinicopathological features. Current prognostic methods, such as the 7th edition of AJCC staging, have limitations. This study aims to construct and validate a comprehensive nomogram integrating multiple c...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2024.1470515/full |
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| author | Yufen Zheng Yuan Yuan Minya Jin Chunlong Wu |
| author_facet | Yufen Zheng Yuan Yuan Minya Jin Chunlong Wu |
| author_sort | Yufen Zheng |
| collection | DOAJ |
| description | PurposeOverall survival (OS) in postoperative breast cancer patients is influenced by various clinicopathological features. Current prognostic methods, such as the 7th edition of AJCC staging, have limitations. This study aims to construct and validate a comprehensive nomogram integrating multiple clinicopathological features to predict OS more accurately in breast cancer patients.MethodsWe identified 60,445 .female patients who underwent breast cancer surgery between January 1, 2011, and December 31, 2015, from the Surveillance, Epidemiology, and End Results (SEER) database, randomly divided into training and internal validation cohorts. Additionally, data from 332 breast cancer surgery patients from four hospitals in Taizhou, Zhejiang Province, were included as an external validation cohort. Kaplan-Meier analysis assessed the impact of clinicopathological features on OS, and multivariable Cox regression identified independent prognostic factors. A nomogram based on these factors was constructed to predict 1-, 3-, and 5-year OS. Model predictive performance was evaluated using C-index, AUC, calibration curves, and decision curves during internal and external validation.ResultsMultivariable Cox regression analysis identified age, pathological grade, AJCC stage, ER status, PR status, and HER2 status as independent prognostic factors used in the nomogram construction. The nomogram achieved a C-index of 0.724 (95% CI, 0.716-0.732) in the training cohorts, 0.717 (95% CI, 0.705-0.729) in the internal validation cohorts, and 0.793 (95% CI, 0.724-0.862) in the external validation cohorts, indicating strong discriminative ability. Calibration curves demonstrated good agreement between predicted and observed outcomes in all validation cohorts. Decision curve analysis showed that the nomogram provided maximum net benefit across all validation cohorts.ConclusionThe nomogram developed in this study integrates multiple clinicopathological features and provides a convenient and accurate tool for predicting individualized OS in breast cancer patients. This tool can optimize treatment strategies and improve patient prognosis. |
| format | Article |
| id | doaj-art-4b3e0d9832e94a7292387617854955c6 |
| institution | Kabale University |
| issn | 2234-943X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj-art-4b3e0d9832e94a7292387617854955c62025-01-22T13:37:30ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2025-01-011410.3389/fonc.2024.14705151470515Nomogram prediction of overall survival in breast cancer patients post-surgery: integrating SEER database and multi-center evidence from ChinaYufen ZhengYuan YuanMinya JinChunlong WuPurposeOverall survival (OS) in postoperative breast cancer patients is influenced by various clinicopathological features. Current prognostic methods, such as the 7th edition of AJCC staging, have limitations. This study aims to construct and validate a comprehensive nomogram integrating multiple clinicopathological features to predict OS more accurately in breast cancer patients.MethodsWe identified 60,445 .female patients who underwent breast cancer surgery between January 1, 2011, and December 31, 2015, from the Surveillance, Epidemiology, and End Results (SEER) database, randomly divided into training and internal validation cohorts. Additionally, data from 332 breast cancer surgery patients from four hospitals in Taizhou, Zhejiang Province, were included as an external validation cohort. Kaplan-Meier analysis assessed the impact of clinicopathological features on OS, and multivariable Cox regression identified independent prognostic factors. A nomogram based on these factors was constructed to predict 1-, 3-, and 5-year OS. Model predictive performance was evaluated using C-index, AUC, calibration curves, and decision curves during internal and external validation.ResultsMultivariable Cox regression analysis identified age, pathological grade, AJCC stage, ER status, PR status, and HER2 status as independent prognostic factors used in the nomogram construction. The nomogram achieved a C-index of 0.724 (95% CI, 0.716-0.732) in the training cohorts, 0.717 (95% CI, 0.705-0.729) in the internal validation cohorts, and 0.793 (95% CI, 0.724-0.862) in the external validation cohorts, indicating strong discriminative ability. Calibration curves demonstrated good agreement between predicted and observed outcomes in all validation cohorts. Decision curve analysis showed that the nomogram provided maximum net benefit across all validation cohorts.ConclusionThe nomogram developed in this study integrates multiple clinicopathological features and provides a convenient and accurate tool for predicting individualized OS in breast cancer patients. This tool can optimize treatment strategies and improve patient prognosis.https://www.frontiersin.org/articles/10.3389/fonc.2024.1470515/fullbreast cancernomogramoverall survivalprognosisSEER database |
| spellingShingle | Yufen Zheng Yuan Yuan Minya Jin Chunlong Wu Nomogram prediction of overall survival in breast cancer patients post-surgery: integrating SEER database and multi-center evidence from China Frontiers in Oncology breast cancer nomogram overall survival prognosis SEER database |
| title | Nomogram prediction of overall survival in breast cancer patients post-surgery: integrating SEER database and multi-center evidence from China |
| title_full | Nomogram prediction of overall survival in breast cancer patients post-surgery: integrating SEER database and multi-center evidence from China |
| title_fullStr | Nomogram prediction of overall survival in breast cancer patients post-surgery: integrating SEER database and multi-center evidence from China |
| title_full_unstemmed | Nomogram prediction of overall survival in breast cancer patients post-surgery: integrating SEER database and multi-center evidence from China |
| title_short | Nomogram prediction of overall survival in breast cancer patients post-surgery: integrating SEER database and multi-center evidence from China |
| title_sort | nomogram prediction of overall survival in breast cancer patients post surgery integrating seer database and multi center evidence from china |
| topic | breast cancer nomogram overall survival prognosis SEER database |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2024.1470515/full |
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