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The VENUSS prognostic model to predict disease recurrence following surgery for non-metastatic papillary renal cell carcinoma: development and evaluation using the ASSURE prospective clinical trial cohort
BACKGROUND: The current World Health Organization classification recognises 12 major subtypes of renal cell carcinoma (RCC). Although these subtypes differ on molecular and clinical levels, they are generally managed as the same disease, simply because they occur in the same organ. Specifically, the...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6775651/ https://www.ncbi.nlm.nih.gov/pubmed/31578141 http://dx.doi.org/10.1186/s12916-019-1419-1 |
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author | Klatte, Tobias Gallagher, Kevin M. Afferi, Luca Volpe, Alessandro Kroeger, Nils Ribback, Silvia McNeill, Alan Riddick, Antony C. P. Armitage, James N. ‘Aho, Tevita F. Eisen, Tim Fife, Kate Bex, Axel Pantuck, Allan J. Stewart, Grant D. |
author_facet | Klatte, Tobias Gallagher, Kevin M. Afferi, Luca Volpe, Alessandro Kroeger, Nils Ribback, Silvia McNeill, Alan Riddick, Antony C. P. Armitage, James N. ‘Aho, Tevita F. Eisen, Tim Fife, Kate Bex, Axel Pantuck, Allan J. Stewart, Grant D. |
author_sort | Klatte, Tobias |
collection | PubMed |
description | BACKGROUND: The current World Health Organization classification recognises 12 major subtypes of renal cell carcinoma (RCC). Although these subtypes differ on molecular and clinical levels, they are generally managed as the same disease, simply because they occur in the same organ. Specifically, there is a paucity of tools to risk-stratify patients with papillary RCC (PRCC). The purpose of this study was to develop and evaluate a tool to risk-stratify patients with clinically non-metastatic PRCC following curative surgery. METHODS: We studied clinicopathological variables and outcomes of 556 patients, who underwent full resection of sporadic, unilateral, non-metastatic (T1–4, N0–1, M0) PRCC at five institutions. Based on multivariable Fine-Gray competing risks regression models, we developed a prognostic scoring system to predict disease recurrence. This was further evaluated in the 150 PRCC patients recruited to the ASSURE trial. We compared the discrimination, calibration and decision-curve clinical net benefit against the Tumour, Node, Metastasis (TNM) stage group, University of California Integrated Staging System (UISS) and the 2018 Leibovich prognostic groups. RESULTS: We developed the VENUSS score from significant variables on multivariable analysis, which were the presence of VEnous tumour thrombus, NUclear grade, Size, T and N Stage. We created three risk groups based on the VENUSS score, with a 5-year cumulative incidence of recurrence equalling 2.9% in low-risk, 15.4% in intermediate-risk and 54.5% in high-risk patients. 91.7% of low-risk patients had oligometastatic recurrent disease, compared to 16.7% of intermediate-risk and 40.0% of high-risk patients. Discrimination, calibration and clinical net benefit from VENUSS appeared to be superior to UISS, TNM and Leibovich prognostic groups. CONCLUSIONS: We developed and tested a prognostic model for patients with clinically non-metastatic PRCC, which is based on routine pathological variables. This model may be superior to standard models and could be used for tailoring postoperative surveillance and defining inclusion for prospective adjuvant clinical trials. |
format | Online Article Text |
id | pubmed-6775651 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-67756512019-10-07 The VENUSS prognostic model to predict disease recurrence following surgery for non-metastatic papillary renal cell carcinoma: development and evaluation using the ASSURE prospective clinical trial cohort Klatte, Tobias Gallagher, Kevin M. Afferi, Luca Volpe, Alessandro Kroeger, Nils Ribback, Silvia McNeill, Alan Riddick, Antony C. P. Armitage, James N. ‘Aho, Tevita F. Eisen, Tim Fife, Kate Bex, Axel Pantuck, Allan J. Stewart, Grant D. BMC Med Research Article BACKGROUND: The current World Health Organization classification recognises 12 major subtypes of renal cell carcinoma (RCC). Although these subtypes differ on molecular and clinical levels, they are generally managed as the same disease, simply because they occur in the same organ. Specifically, there is a paucity of tools to risk-stratify patients with papillary RCC (PRCC). The purpose of this study was to develop and evaluate a tool to risk-stratify patients with clinically non-metastatic PRCC following curative surgery. METHODS: We studied clinicopathological variables and outcomes of 556 patients, who underwent full resection of sporadic, unilateral, non-metastatic (T1–4, N0–1, M0) PRCC at five institutions. Based on multivariable Fine-Gray competing risks regression models, we developed a prognostic scoring system to predict disease recurrence. This was further evaluated in the 150 PRCC patients recruited to the ASSURE trial. We compared the discrimination, calibration and decision-curve clinical net benefit against the Tumour, Node, Metastasis (TNM) stage group, University of California Integrated Staging System (UISS) and the 2018 Leibovich prognostic groups. RESULTS: We developed the VENUSS score from significant variables on multivariable analysis, which were the presence of VEnous tumour thrombus, NUclear grade, Size, T and N Stage. We created three risk groups based on the VENUSS score, with a 5-year cumulative incidence of recurrence equalling 2.9% in low-risk, 15.4% in intermediate-risk and 54.5% in high-risk patients. 91.7% of low-risk patients had oligometastatic recurrent disease, compared to 16.7% of intermediate-risk and 40.0% of high-risk patients. Discrimination, calibration and clinical net benefit from VENUSS appeared to be superior to UISS, TNM and Leibovich prognostic groups. CONCLUSIONS: We developed and tested a prognostic model for patients with clinically non-metastatic PRCC, which is based on routine pathological variables. This model may be superior to standard models and could be used for tailoring postoperative surveillance and defining inclusion for prospective adjuvant clinical trials. BioMed Central 2019-10-03 /pmc/articles/PMC6775651/ /pubmed/31578141 http://dx.doi.org/10.1186/s12916-019-1419-1 Text en © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Klatte, Tobias Gallagher, Kevin M. Afferi, Luca Volpe, Alessandro Kroeger, Nils Ribback, Silvia McNeill, Alan Riddick, Antony C. P. Armitage, James N. ‘Aho, Tevita F. Eisen, Tim Fife, Kate Bex, Axel Pantuck, Allan J. Stewart, Grant D. The VENUSS prognostic model to predict disease recurrence following surgery for non-metastatic papillary renal cell carcinoma: development and evaluation using the ASSURE prospective clinical trial cohort |
title | The VENUSS prognostic model to predict disease recurrence following surgery for non-metastatic papillary renal cell carcinoma: development and evaluation using the ASSURE prospective clinical trial cohort |
title_full | The VENUSS prognostic model to predict disease recurrence following surgery for non-metastatic papillary renal cell carcinoma: development and evaluation using the ASSURE prospective clinical trial cohort |
title_fullStr | The VENUSS prognostic model to predict disease recurrence following surgery for non-metastatic papillary renal cell carcinoma: development and evaluation using the ASSURE prospective clinical trial cohort |
title_full_unstemmed | The VENUSS prognostic model to predict disease recurrence following surgery for non-metastatic papillary renal cell carcinoma: development and evaluation using the ASSURE prospective clinical trial cohort |
title_short | The VENUSS prognostic model to predict disease recurrence following surgery for non-metastatic papillary renal cell carcinoma: development and evaluation using the ASSURE prospective clinical trial cohort |
title_sort | venuss prognostic model to predict disease recurrence following surgery for non-metastatic papillary renal cell carcinoma: development and evaluation using the assure prospective clinical trial cohort |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6775651/ https://www.ncbi.nlm.nih.gov/pubmed/31578141 http://dx.doi.org/10.1186/s12916-019-1419-1 |
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