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A preoperative nomogram predicting the pseudocapsule status in localized renal cell carcinoma
BACKGROUND: Tumor enucleation (TE) surgery for localized renal cell carcinoma (RCC) relies on a complete peritumoral pseudocapsule (PC). Study objective was to develop a preoperative model to predict PC status. METHODS: The prediction model was developed in a cohort that consisted of 170 patients wi...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7214989/ https://www.ncbi.nlm.nih.gov/pubmed/32420152 http://dx.doi.org/10.21037/tau.2020.01.26 |
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author | Hu, Jiao Chen, Jinbo Li, Huihuang He, Tongchen Deng, Hao Gong, Guanghui Cui, Yu Liu, Peihua Ren, Wenbiao Zhou, Xu Li, Chao Zu, Xiongbing |
author_facet | Hu, Jiao Chen, Jinbo Li, Huihuang He, Tongchen Deng, Hao Gong, Guanghui Cui, Yu Liu, Peihua Ren, Wenbiao Zhou, Xu Li, Chao Zu, Xiongbing |
author_sort | Hu, Jiao |
collection | PubMed |
description | BACKGROUND: Tumor enucleation (TE) surgery for localized renal cell carcinoma (RCC) relies on a complete peritumoral pseudocapsule (PC). Study objective was to develop a preoperative model to predict PC status. METHODS: The prediction model was developed in a cohort that consisted of 170 patients with localized RCC, and data was gathered from 2010 to 2015. Multivariable logistic regression analysis and R were used to generate this prediction model. The statistical performance was assessed with respect to the calibration, discrimination, and clinical usefulness. RESULTS: The prediction model incorporated the systemic inflammatory markers [neutrophil-lymphocyte ratio (NLR); albumin-globulin ratio (AGR)], CT imaging features (tumor size and necrosis), and clinical risk factors (BMI). The model showed good discrimination, with a C-index of 0.85 (0.78–0.91), and good calibration (P=0.60). The sensitivity and specificity were 62% and 94% respectively. Decision curves and clinical impact curve demonstrated that the current model was clinically useful. CONCLUSIONS: We constructed a model that incorporated both the systematic inflammatory markers and clinical risk factors. It can be conveniently used to preoperatively predict the individualized risk of PC invasion and identify the best candidates to receive TE surgery. |
format | Online Article Text |
id | pubmed-7214989 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-72149892020-05-15 A preoperative nomogram predicting the pseudocapsule status in localized renal cell carcinoma Hu, Jiao Chen, Jinbo Li, Huihuang He, Tongchen Deng, Hao Gong, Guanghui Cui, Yu Liu, Peihua Ren, Wenbiao Zhou, Xu Li, Chao Zu, Xiongbing Transl Androl Urol Original Article BACKGROUND: Tumor enucleation (TE) surgery for localized renal cell carcinoma (RCC) relies on a complete peritumoral pseudocapsule (PC). Study objective was to develop a preoperative model to predict PC status. METHODS: The prediction model was developed in a cohort that consisted of 170 patients with localized RCC, and data was gathered from 2010 to 2015. Multivariable logistic regression analysis and R were used to generate this prediction model. The statistical performance was assessed with respect to the calibration, discrimination, and clinical usefulness. RESULTS: The prediction model incorporated the systemic inflammatory markers [neutrophil-lymphocyte ratio (NLR); albumin-globulin ratio (AGR)], CT imaging features (tumor size and necrosis), and clinical risk factors (BMI). The model showed good discrimination, with a C-index of 0.85 (0.78–0.91), and good calibration (P=0.60). The sensitivity and specificity were 62% and 94% respectively. Decision curves and clinical impact curve demonstrated that the current model was clinically useful. CONCLUSIONS: We constructed a model that incorporated both the systematic inflammatory markers and clinical risk factors. It can be conveniently used to preoperatively predict the individualized risk of PC invasion and identify the best candidates to receive TE surgery. AME Publishing Company 2020-04 /pmc/articles/PMC7214989/ /pubmed/32420152 http://dx.doi.org/10.21037/tau.2020.01.26 Text en 2020 Translational Andrology and Urology. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Hu, Jiao Chen, Jinbo Li, Huihuang He, Tongchen Deng, Hao Gong, Guanghui Cui, Yu Liu, Peihua Ren, Wenbiao Zhou, Xu Li, Chao Zu, Xiongbing A preoperative nomogram predicting the pseudocapsule status in localized renal cell carcinoma |
title | A preoperative nomogram predicting the pseudocapsule status in localized renal cell carcinoma |
title_full | A preoperative nomogram predicting the pseudocapsule status in localized renal cell carcinoma |
title_fullStr | A preoperative nomogram predicting the pseudocapsule status in localized renal cell carcinoma |
title_full_unstemmed | A preoperative nomogram predicting the pseudocapsule status in localized renal cell carcinoma |
title_short | A preoperative nomogram predicting the pseudocapsule status in localized renal cell carcinoma |
title_sort | preoperative nomogram predicting the pseudocapsule status in localized renal cell carcinoma |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7214989/ https://www.ncbi.nlm.nih.gov/pubmed/32420152 http://dx.doi.org/10.21037/tau.2020.01.26 |
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