Construction and Validation of Novel Prediction Tools Based on Large Population-Based Database to Predict the Prognosis of Urachal Cancer After Surgery
BackgroundUrachal cancer is a rare neoplasm in the urological system. To our knowledge, no published study has explored to establish a model for predicting the prognosis of urachal cancer. The present study aims to develop and validate nomograms for predicting the prognosis of urachal cancer based o...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-09-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2021.718691/full |
| _version_ | 1819123128734842880 |
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| author | Xiaowen Yu Xiaowen Yu Chong Ma Maoyu Wang Yidie Ying Zhensheng Zhang Xing Ai Linhui Wang Shuxiong Zeng Chuanliang Xu |
| author_facet | Xiaowen Yu Xiaowen Yu Chong Ma Maoyu Wang Yidie Ying Zhensheng Zhang Xing Ai Linhui Wang Shuxiong Zeng Chuanliang Xu |
| author_sort | Xiaowen Yu |
| collection | DOAJ |
| description | BackgroundUrachal cancer is a rare neoplasm in the urological system. To our knowledge, no published study has explored to establish a model for predicting the prognosis of urachal cancer. The present study aims to develop and validate nomograms for predicting the prognosis of urachal cancer based on clinicopathological parameters.MethodsBased on the data from the Surveillance, Epidemiology, and End Results database, 445 patients diagnosed with urachal cancer between 1975 and 2018 were identified as training and internal validation cohort; 84 patients diagnosed as urachal cancer from 2001 to 2020 in two medical centers were collected as external validation cohort. Nomograms were developed using a multivariate Cox proportional hazards regression analysis in the training cohort, and their performance was evaluated in terms of its discriminative ability, calibration, and clinical usefulness by statistical analysis.ResultsThree nomograms based on tumor–node–metastasis (TNM), Sheldon and Mayo staging system were developed for predicting cancer-specific survival (CSS) of urachal cancer; these nomograms all showed similar calibration and discrimination ability. Further internal (c-index 0.78) and external (c-index 0.81) validation suggested that Sheldon model had superior discrimination and calibration ability in predicting CSS than the other two models. Moreover, we found that the Sheldon model was able to successfully classify patients into different risk of mortality both in internal and external validation cohorts. Decision curve analysis proved that the nomogram was clinically useful and applicable.ConclusionsThe nomogram model with Sheldon staging system was recommended for predicting the prognosis of urachal cancer. The proposed nomograms have promising clinical applicability to help clinicians on individualized patient counseling, decision-making, and clinical trial designing. |
| first_indexed | 2024-12-22T07:03:26Z |
| format | Article |
| id | doaj.art-001d07208eec44378ed0ccfa4de90729 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-22T07:03:26Z |
| publishDate | 2021-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-001d07208eec44378ed0ccfa4de907292022-12-21T18:34:43ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2021-09-011110.3389/fonc.2021.718691718691Construction and Validation of Novel Prediction Tools Based on Large Population-Based Database to Predict the Prognosis of Urachal Cancer After SurgeryXiaowen Yu0Xiaowen Yu1Chong Ma2Maoyu Wang3Yidie Ying4Zhensheng Zhang5Xing Ai6Linhui Wang7Shuxiong Zeng8Chuanliang Xu9Department of Urology, Changhai Hospital, Naval Medical University, Shanghai, ChinaDepartment of Geriatrics, Changhai Hospital, Naval Medical University, Shanghai, ChinaSenior Department of Urology, The Third Medical Center of PLA General Hospital, Beijing, ChinaDepartment of Urology, Changhai Hospital, Naval Medical University, Shanghai, ChinaDepartment of Urology, Changhai Hospital, Naval Medical University, Shanghai, ChinaDepartment of Urology, Changhai Hospital, Naval Medical University, Shanghai, ChinaSenior Department of Urology, The Third Medical Center of PLA General Hospital, Beijing, ChinaDepartment of Urology, Changhai Hospital, Naval Medical University, Shanghai, ChinaDepartment of Urology, Changhai Hospital, Naval Medical University, Shanghai, ChinaDepartment of Urology, Changhai Hospital, Naval Medical University, Shanghai, ChinaBackgroundUrachal cancer is a rare neoplasm in the urological system. To our knowledge, no published study has explored to establish a model for predicting the prognosis of urachal cancer. The present study aims to develop and validate nomograms for predicting the prognosis of urachal cancer based on clinicopathological parameters.MethodsBased on the data from the Surveillance, Epidemiology, and End Results database, 445 patients diagnosed with urachal cancer between 1975 and 2018 were identified as training and internal validation cohort; 84 patients diagnosed as urachal cancer from 2001 to 2020 in two medical centers were collected as external validation cohort. Nomograms were developed using a multivariate Cox proportional hazards regression analysis in the training cohort, and their performance was evaluated in terms of its discriminative ability, calibration, and clinical usefulness by statistical analysis.ResultsThree nomograms based on tumor–node–metastasis (TNM), Sheldon and Mayo staging system were developed for predicting cancer-specific survival (CSS) of urachal cancer; these nomograms all showed similar calibration and discrimination ability. Further internal (c-index 0.78) and external (c-index 0.81) validation suggested that Sheldon model had superior discrimination and calibration ability in predicting CSS than the other two models. Moreover, we found that the Sheldon model was able to successfully classify patients into different risk of mortality both in internal and external validation cohorts. Decision curve analysis proved that the nomogram was clinically useful and applicable.ConclusionsThe nomogram model with Sheldon staging system was recommended for predicting the prognosis of urachal cancer. The proposed nomograms have promising clinical applicability to help clinicians on individualized patient counseling, decision-making, and clinical trial designing.https://www.frontiersin.org/articles/10.3389/fonc.2021.718691/fullnomogrampredictorsprognosisurachal cancerSEER |
| spellingShingle | Xiaowen Yu Xiaowen Yu Chong Ma Maoyu Wang Yidie Ying Zhensheng Zhang Xing Ai Linhui Wang Shuxiong Zeng Chuanliang Xu Construction and Validation of Novel Prediction Tools Based on Large Population-Based Database to Predict the Prognosis of Urachal Cancer After Surgery Frontiers in Oncology nomogram predictors prognosis urachal cancer SEER |
| title | Construction and Validation of Novel Prediction Tools Based on Large Population-Based Database to Predict the Prognosis of Urachal Cancer After Surgery |
| title_full | Construction and Validation of Novel Prediction Tools Based on Large Population-Based Database to Predict the Prognosis of Urachal Cancer After Surgery |
| title_fullStr | Construction and Validation of Novel Prediction Tools Based on Large Population-Based Database to Predict the Prognosis of Urachal Cancer After Surgery |
| title_full_unstemmed | Construction and Validation of Novel Prediction Tools Based on Large Population-Based Database to Predict the Prognosis of Urachal Cancer After Surgery |
| title_short | Construction and Validation of Novel Prediction Tools Based on Large Population-Based Database to Predict the Prognosis of Urachal Cancer After Surgery |
| title_sort | construction and validation of novel prediction tools based on large population based database to predict the prognosis of urachal cancer after surgery |
| topic | nomogram predictors prognosis urachal cancer SEER |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2021.718691/full |
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