Cargando…
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...
Autores principales: | , , , , , |
---|---|
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 |
_version_ | 1783247662693220352 |
---|---|
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. |
format | Online Article Text |
id | pubmed-5494346 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | The Korean Urological Association |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT baumantylerm patientandnonradiographictumorcharacteristicspredictinglipidpoorangiomyolipomainsmallrenalmassesintroducingthebearsindex AT potretzkeaaronm patientandnonradiographictumorcharacteristicspredictinglipidpoorangiomyolipomainsmallrenalmassesintroducingthebearsindex AT wrightalecj patientandnonradiographictumorcharacteristicspredictinglipidpoorangiomyolipomainsmallrenalmassesintroducingthebearsindex AT vetterjoelm patientandnonradiographictumorcharacteristicspredictinglipidpoorangiomyolipomainsmallrenalmassesintroducingthebearsindex AT potretzketheodoraa patientandnonradiographictumorcharacteristicspredictinglipidpoorangiomyolipomainsmallrenalmassesintroducingthebearsindex AT figenshaursherburne patientandnonradiographictumorcharacteristicspredictinglipidpoorangiomyolipomainsmallrenalmassesintroducingthebearsindex |