Predicting Cancer-Specific Survival Among Patients With Prostate Cancer After Radical Prostatectomy Based on the Competing Risk Model: Population-Based Study

Introduction: We aimed to develop an easy-to-use individual survival prognostication tool based on competing risk analyses to predict the risk of 5-year cancer-specific death after radical prostatectomy for patients with prostate cancer (PCa).Methods: We obtained the data from the Surveillance, Epid...

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Autores principales:	Xianghong Zhou, Shi Qiu, Kun Jin, Qiming Yuan, Di Jin, Zilong Zhang, Xiaonan Zheng, Jiakun Li, Qiang Wei, Lu Yang
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	competing risk analyses prostate cancer radical prostatectomy post-surgery predicting model Surgery RD1-811
Acceso en línea:	https://doaj.org/article/e9990c8ac51c45d68af8b0f40de9c3ed
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spelling	oai:doaj.org-article:e9990c8ac51c45d68af8b0f40de9c3ed2021-12-01T05:00:27ZPredicting Cancer-Specific Survival Among Patients With Prostate Cancer After Radical Prostatectomy Based on the Competing Risk Model: Population-Based Study2296-875X10.3389/fsurg.2021.770169https://doaj.org/article/e9990c8ac51c45d68af8b0f40de9c3ed2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fsurg.2021.770169/fullhttps://doaj.org/toc/2296-875XIntroduction: We aimed to develop an easy-to-use individual survival prognostication tool based on competing risk analyses to predict the risk of 5-year cancer-specific death after radical prostatectomy for patients with prostate cancer (PCa).Methods: We obtained the data from the Surveillance, Epidemiology, and End Results (SEER) database (2004–2016). The main variables obtained included age at diagnosis, marital status, race, pathological extension, regional lymphonode status, prostate specific antigen level, pathological Gleason Score. In order to reveal the independent prognostic factors. The cumulative incidence function was used as the univariable competing risk analyses and The Fine and Gray's proportional subdistribution hazard approach was used as the multivariable competing risk analyses. With these factors, a nomogram and risk stratification based on the nomogram was established. Concordance index (C-index) and calibration curves were used for validation.Results: A total of 95,812 patients were included and divided into training cohort (n = 67,072) and validation cohort (n = 28,740). Seven independent prognostic factors including age, race, marital status, pathological extension, regional lymphonode status, PSA level, and pathological GS were used to construct the nomogram. In the training cohort, the C-index was 0.828 (%95CI, 0.812–0.844), and the C-index was 0.838 (%95CI, 0.813–0.863) in the validation cohort. The results of the cumulative incidence function showed that the discrimination of risk stratification based on nomogram is better than that of the risk stratification system based on D'Amico risk stratification.Conclusions: We successfully developed the first competing risk nomogram to predict the risk of cancer-specific death after surgery for patients with PCa. It has the potential to help clinicians improve post-operative management of patients.Xianghong ZhouShi QiuKun JinQiming YuanDi JinZilong ZhangXiaonan ZhengJiakun LiQiang WeiLu YangFrontiers Media S.A.articlecompeting risk analysesprostate cancerradical prostatectomypost-surgerypredicting modelSurgeryRD1-811ENFrontiers in Surgery, Vol 8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	competing risk analyses prostate cancer radical prostatectomy post-surgery predicting model Surgery RD1-811
spellingShingle	competing risk analyses prostate cancer radical prostatectomy post-surgery predicting model Surgery RD1-811 Xianghong Zhou Shi Qiu Kun Jin Qiming Yuan Di Jin Zilong Zhang Xiaonan Zheng Jiakun Li Qiang Wei Lu Yang Predicting Cancer-Specific Survival Among Patients With Prostate Cancer After Radical Prostatectomy Based on the Competing Risk Model: Population-Based Study
description	Introduction: We aimed to develop an easy-to-use individual survival prognostication tool based on competing risk analyses to predict the risk of 5-year cancer-specific death after radical prostatectomy for patients with prostate cancer (PCa).Methods: We obtained the data from the Surveillance, Epidemiology, and End Results (SEER) database (2004–2016). The main variables obtained included age at diagnosis, marital status, race, pathological extension, regional lymphonode status, prostate specific antigen level, pathological Gleason Score. In order to reveal the independent prognostic factors. The cumulative incidence function was used as the univariable competing risk analyses and The Fine and Gray's proportional subdistribution hazard approach was used as the multivariable competing risk analyses. With these factors, a nomogram and risk stratification based on the nomogram was established. Concordance index (C-index) and calibration curves were used for validation.Results: A total of 95,812 patients were included and divided into training cohort (n = 67,072) and validation cohort (n = 28,740). Seven independent prognostic factors including age, race, marital status, pathological extension, regional lymphonode status, PSA level, and pathological GS were used to construct the nomogram. In the training cohort, the C-index was 0.828 (%95CI, 0.812–0.844), and the C-index was 0.838 (%95CI, 0.813–0.863) in the validation cohort. The results of the cumulative incidence function showed that the discrimination of risk stratification based on nomogram is better than that of the risk stratification system based on D'Amico risk stratification.Conclusions: We successfully developed the first competing risk nomogram to predict the risk of cancer-specific death after surgery for patients with PCa. It has the potential to help clinicians improve post-operative management of patients.
format	article
author	Xianghong Zhou Shi Qiu Kun Jin Qiming Yuan Di Jin Zilong Zhang Xiaonan Zheng Jiakun Li Qiang Wei Lu Yang
author_facet	Xianghong Zhou Shi Qiu Kun Jin Qiming Yuan Di Jin Zilong Zhang Xiaonan Zheng Jiakun Li Qiang Wei Lu Yang
author_sort	Xianghong Zhou
title	Predicting Cancer-Specific Survival Among Patients With Prostate Cancer After Radical Prostatectomy Based on the Competing Risk Model: Population-Based Study
title_short	Predicting Cancer-Specific Survival Among Patients With Prostate Cancer After Radical Prostatectomy Based on the Competing Risk Model: Population-Based Study
title_full	Predicting Cancer-Specific Survival Among Patients With Prostate Cancer After Radical Prostatectomy Based on the Competing Risk Model: Population-Based Study
title_fullStr	Predicting Cancer-Specific Survival Among Patients With Prostate Cancer After Radical Prostatectomy Based on the Competing Risk Model: Population-Based Study
title_full_unstemmed	Predicting Cancer-Specific Survival Among Patients With Prostate Cancer After Radical Prostatectomy Based on the Competing Risk Model: Population-Based Study
title_sort	predicting cancer-specific survival among patients with prostate cancer after radical prostatectomy based on the competing risk model: population-based study
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/e9990c8ac51c45d68af8b0f40de9c3ed
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Predicting Cancer-Specific Survival Among Patients With Prostate Cancer After Radical Prostatectomy Based on the Competing Risk Model: Population-Based Study

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