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A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients

Although several models have been developed to predict the probability of Gleason sum upgrading between biopsy and radical prostatectomy specimens, most of these models are restricted to prostate-specific antigen screening-detected prostate cancer. This study aimed to build a nomogram for the predic...

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Autores principales: Wang, Jin-You, Zhu, Yao, Wang, Chao-Fu, Zhang, Shi-Lin, Dai, Bo, Ye, Ding-Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sun Yat-sen University Cancer Center 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4026544/
https://www.ncbi.nlm.nih.gov/pubmed/24559852
http://dx.doi.org/10.5732/cjc.013.10137
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author Wang, Jin-You
Zhu, Yao
Wang, Chao-Fu
Zhang, Shi-Lin
Dai, Bo
Ye, Ding-Wei
author_facet Wang, Jin-You
Zhu, Yao
Wang, Chao-Fu
Zhang, Shi-Lin
Dai, Bo
Ye, Ding-Wei
author_sort Wang, Jin-You
collection PubMed
description Although several models have been developed to predict the probability of Gleason sum upgrading between biopsy and radical prostatectomy specimens, most of these models are restricted to prostate-specific antigen screening-detected prostate cancer. This study aimed to build a nomogram for the prediction of Gleason sum upgrading in clinically diagnosed prostate cancer. The study cohort comprised 269 Chinese prostate cancer patients who underwent prostate biopsy with a minimum of 10 cores and were subsequently treated with radical prostatectomy. Of all included patients, 220 (81.8%) were referred with clinical symptoms. The prostate-specific antigen level, primary and secondary biopsy Gleason scores, and clinical T category were used in a multivariate logistic regression model to predict the probability of Gleason sum upgrading. The developed nomogram was validated internally. Gleason sum upgrading was observed in 90 (33.5%) patients. Our nomogram showed a bootstrap-corrected concordance index of 0.789 and good calibration using 4 readily available variables. The nomogram also demonstrated satisfactory statistical performance for predicting significant upgrading. External validation of the nomogram published by Chun et al. in our cohort showed a marked discordance between the observed and predicted probabilities of Gleason sum upgrading. In summary, a new nomogram to predict Gleason sum upgrading in clinically diagnosed prostate cancer was developed, and it demonstrated good statistical performance upon internal validation.
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spelling pubmed-40265442014-05-20 A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients Wang, Jin-You Zhu, Yao Wang, Chao-Fu Zhang, Shi-Lin Dai, Bo Ye, Ding-Wei Chin J Cancer Original Article Although several models have been developed to predict the probability of Gleason sum upgrading between biopsy and radical prostatectomy specimens, most of these models are restricted to prostate-specific antigen screening-detected prostate cancer. This study aimed to build a nomogram for the prediction of Gleason sum upgrading in clinically diagnosed prostate cancer. The study cohort comprised 269 Chinese prostate cancer patients who underwent prostate biopsy with a minimum of 10 cores and were subsequently treated with radical prostatectomy. Of all included patients, 220 (81.8%) were referred with clinical symptoms. The prostate-specific antigen level, primary and secondary biopsy Gleason scores, and clinical T category were used in a multivariate logistic regression model to predict the probability of Gleason sum upgrading. The developed nomogram was validated internally. Gleason sum upgrading was observed in 90 (33.5%) patients. Our nomogram showed a bootstrap-corrected concordance index of 0.789 and good calibration using 4 readily available variables. The nomogram also demonstrated satisfactory statistical performance for predicting significant upgrading. External validation of the nomogram published by Chun et al. in our cohort showed a marked discordance between the observed and predicted probabilities of Gleason sum upgrading. In summary, a new nomogram to predict Gleason sum upgrading in clinically diagnosed prostate cancer was developed, and it demonstrated good statistical performance upon internal validation. Sun Yat-sen University Cancer Center 2014-05 /pmc/articles/PMC4026544/ /pubmed/24559852 http://dx.doi.org/10.5732/cjc.013.10137 Text en Chinese Journal of Cancer http://creativecommons.org/licenses/by-nc-sa/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License, which allows readers to alter, transform, or build upon the article and then distribute the resulting work under the same or similar license to this one. The work must be attributed back to the original author and commercial use is not permitted without specific permission.
spellingShingle Original Article
Wang, Jin-You
Zhu, Yao
Wang, Chao-Fu
Zhang, Shi-Lin
Dai, Bo
Ye, Ding-Wei
A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients
title A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients
title_full A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients
title_fullStr A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients
title_full_unstemmed A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients
title_short A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients
title_sort nomogram to predict gleason sum upgrading of clinically diagnosed localized prostate cancer among chinese patients
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4026544/
https://www.ncbi.nlm.nih.gov/pubmed/24559852
http://dx.doi.org/10.5732/cjc.013.10137
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