Investig Clin Urol.  2017 Jul;58(4):235-240. 10.4111/icu.2017.58.4.235.

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

• Bauman TM
• Potretzke
• Wright AJ
• Vetter JM
• Potretzke
• Figenshau

• KMID: 2410289
• DOI: http://doi.org/10.4111/icu.2017.58.4.235

Abstract

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.

Keyword

Angiomyolipoma; Decision support techniques; Nephrectomy; Renal cell carcinoma

MeSH Terms

Angiomyolipoma*
Carcinoma, Renal Cell
Decision Support Techniques
Female
Humans
Incidence
Logistic Models
Nephrectomy
Pathology
Prospective Studies
Risk Factors

Figure

• 

  Fig. 1 Receiver operating characteristic analysis of the ability of the BEnign Angiomyolipoma Renal Susceptibility (BEARS) index to differentiate lipid-poor angiomyolipoma and renal cell carcinoma in renal masses ≤4 cm. The BEARS index was calculated for each patient using sex, tumor size, and age at surgery. The index significantly predicted lipid-poor angiomyolipoma histology after partial nephrectomy (area under the curve [AUC]=0.84; p<0.0001).

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