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Patient and nonradiographic tumor characteristics predicting lipid-poor angiomyolipoma in small renal masses: Introducing the BEARS index

PURPOSE: To create a simple model using clinical variables for predicting lipid-poor angiomyolipoma (AML) in patients with small renal masses presumed to be renal cell carcinoma (RCC) from preoperative imaging. MATERIALS AND METHODS: A series of patients undergoing partial nephrectomy (PN) for renal...

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Autores principales: Bauman, Tyler M., Potretzke, Aaron M., Wright, Alec J., Vetter, Joel M., Potretzke, Theodora A., Figenshau, R. Sherburne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Urological Association 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5494346/
https://www.ncbi.nlm.nih.gov/pubmed/28681032
http://dx.doi.org/10.4111/icu.2017.58.4.235
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author Bauman, Tyler M.
Potretzke, Aaron M.
Wright, Alec J.
Vetter, Joel M.
Potretzke, Theodora A.
Figenshau, R. Sherburne
author_facet Bauman, Tyler M.
Potretzke, Aaron M.
Wright, Alec J.
Vetter, Joel M.
Potretzke, Theodora A.
Figenshau, R. Sherburne
author_sort Bauman, Tyler M.
collection PubMed
description PURPOSE: To create a simple model using clinical variables for predicting lipid-poor angiomyolipoma (AML) in patients with small renal masses presumed to be renal cell carcinoma (RCC) from preoperative imaging. MATERIALS AND METHODS: A series of patients undergoing partial nephrectomy (PN) for renal masses ≤4 cm was identified using a prospectively maintained database. Patients were excluded if standard preoperative imaging was not consistent with RCC. Chi square and Mann-Whitney U analyses were used to evaluate differences in characteristics between patients with AML and other types of pathology. A logistic regression model was constructed for multivariable analysis of predictors of lipid-poor AML. RESULTS: A total of 730 patients were identified that underwent PN for renal masses ≤4 cm between 2007–2015, including 35 with lipid-poor AML and 620 with RCC. In multivariable analysis, the following features predicted AML: female sex (odds ratio, 6.89; 95% confidence interval, 2.35–20.92; p<0.001), age <56 years (2.84; 1.21–6.66; p=0.02), and tumor size <2 cm (5.87; 2.70–12.77; p<0.001). Sex, age, and tumor size were used to construct the BEnign Angiomyolipoma Renal Susceptibility (BEARS) index with the following point values for each particular risk factor: female sex (2 points), age <56 years (1 point), and tumor size <2 cm (2 points). Within the study population, the BEARS index distinguished AML from malignant lesions with an area under the curve of 0.84. CONCLUSIONS: Young female patients with small tumors are at risk for having lipid-poor AML despite preoperative imaging consistent with RCC. Identification of these patients may reduce the incidence of unnecessary PN for benign renal lesions.
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spelling pubmed-54943462017-07-05 Patient and nonradiographic tumor characteristics predicting lipid-poor angiomyolipoma in small renal masses: Introducing the BEARS index Bauman, Tyler M. Potretzke, Aaron M. Wright, Alec J. Vetter, Joel M. Potretzke, Theodora A. Figenshau, R. Sherburne Investig Clin Urol Original Article PURPOSE: To create a simple model using clinical variables for predicting lipid-poor angiomyolipoma (AML) in patients with small renal masses presumed to be renal cell carcinoma (RCC) from preoperative imaging. MATERIALS AND METHODS: A series of patients undergoing partial nephrectomy (PN) for renal masses ≤4 cm was identified using a prospectively maintained database. Patients were excluded if standard preoperative imaging was not consistent with RCC. Chi square and Mann-Whitney U analyses were used to evaluate differences in characteristics between patients with AML and other types of pathology. A logistic regression model was constructed for multivariable analysis of predictors of lipid-poor AML. RESULTS: A total of 730 patients were identified that underwent PN for renal masses ≤4 cm between 2007–2015, including 35 with lipid-poor AML and 620 with RCC. In multivariable analysis, the following features predicted AML: female sex (odds ratio, 6.89; 95% confidence interval, 2.35–20.92; p<0.001), age <56 years (2.84; 1.21–6.66; p=0.02), and tumor size <2 cm (5.87; 2.70–12.77; p<0.001). Sex, age, and tumor size were used to construct the BEnign Angiomyolipoma Renal Susceptibility (BEARS) index with the following point values for each particular risk factor: female sex (2 points), age <56 years (1 point), and tumor size <2 cm (2 points). Within the study population, the BEARS index distinguished AML from malignant lesions with an area under the curve of 0.84. CONCLUSIONS: Young female patients with small tumors are at risk for having lipid-poor AML despite preoperative imaging consistent with RCC. Identification of these patients may reduce the incidence of unnecessary PN for benign renal lesions. The Korean Urological Association 2017-07 2017-06-27 /pmc/articles/PMC5494346/ /pubmed/28681032 http://dx.doi.org/10.4111/icu.2017.58.4.235 Text en © The Korean Urological Association, 2017 http://creativecommons.org/licenses/by-nc/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Bauman, Tyler M.
Potretzke, Aaron M.
Wright, Alec J.
Vetter, Joel M.
Potretzke, Theodora A.
Figenshau, R. Sherburne
Patient and nonradiographic tumor characteristics predicting lipid-poor angiomyolipoma in small renal masses: Introducing the BEARS index
title Patient and nonradiographic tumor characteristics predicting lipid-poor angiomyolipoma in small renal masses: Introducing the BEARS index
title_full Patient and nonradiographic tumor characteristics predicting lipid-poor angiomyolipoma in small renal masses: Introducing the BEARS index
title_fullStr Patient and nonradiographic tumor characteristics predicting lipid-poor angiomyolipoma in small renal masses: Introducing the BEARS index
title_full_unstemmed Patient and nonradiographic tumor characteristics predicting lipid-poor angiomyolipoma in small renal masses: Introducing the BEARS index
title_short Patient and nonradiographic tumor characteristics predicting lipid-poor angiomyolipoma in small renal masses: Introducing the BEARS index
title_sort patient and nonradiographic tumor characteristics predicting lipid-poor angiomyolipoma in small renal masses: introducing the bears index
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5494346/
https://www.ncbi.nlm.nih.gov/pubmed/28681032
http://dx.doi.org/10.4111/icu.2017.58.4.235
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