Surgical treatment of small renal masses (RMs) is still characterized by a non-negligible rate of benign histology, ultimately resulting in overtreatment. Since the risk of kidney cancer increases with age and the risk of malignancy usually increases with tumor size, we created a model based on patient age, RM size, and their interaction for predicting malignant histology. As male sex is associated with a higher risk of renal malignancy, we also stratified our analyses by sex. We used data for 2252 patients with cT1N0M0 disease (1551 male [69%], 701 female [31%]). On logistic regression, both age and RM size were predictors of malignant histology. For males, the odds ratio (OR) was 1.82 (95% confidence interval [CI] 1.78-2.80) for age and 2.04 (95% CI 1.69-2.47) for RM size; for females, the OR was 1.82 (95% CI 1.78-2.80) for age and 2.04 (95% CI 1.69-2.47) for RM size (all p ≤ 0.007), with a significant continuous-by-continuous interaction between them (p < 0.001) in both models. On decision curve analysis, the model demonstrated clinical utility for predicting malignancy at a probability of <55% for males and <60% for females. Individuals with lower probability should be considered for renal biopsy and those with higher probability for upfront surgery. The model was also more informative than RM size alone in predicting malignancy, which currently represents the only absolute criterion for active surveillance eligibility. PATIENT SUMMARY: In this study we analyzed the correlation between age and tumor size for predicting tumor malignancy. The aim in management is to balance the utility of performing a biopsy and the appropriateness of upfront surgery against the ultimate goal of decreasing overtreatment.

How to Select the Optimal Candidates for Renal Mass Biopsy

Falagario U. G.;
2021-01-01

Abstract

Surgical treatment of small renal masses (RMs) is still characterized by a non-negligible rate of benign histology, ultimately resulting in overtreatment. Since the risk of kidney cancer increases with age and the risk of malignancy usually increases with tumor size, we created a model based on patient age, RM size, and their interaction for predicting malignant histology. As male sex is associated with a higher risk of renal malignancy, we also stratified our analyses by sex. We used data for 2252 patients with cT1N0M0 disease (1551 male [69%], 701 female [31%]). On logistic regression, both age and RM size were predictors of malignant histology. For males, the odds ratio (OR) was 1.82 (95% confidence interval [CI] 1.78-2.80) for age and 2.04 (95% CI 1.69-2.47) for RM size; for females, the OR was 1.82 (95% CI 1.78-2.80) for age and 2.04 (95% CI 1.69-2.47) for RM size (all p ≤ 0.007), with a significant continuous-by-continuous interaction between them (p < 0.001) in both models. On decision curve analysis, the model demonstrated clinical utility for predicting malignancy at a probability of <55% for males and <60% for females. Individuals with lower probability should be considered for renal biopsy and those with higher probability for upfront surgery. The model was also more informative than RM size alone in predicting malignancy, which currently represents the only absolute criterion for active surveillance eligibility. PATIENT SUMMARY: In this study we analyzed the correlation between age and tumor size for predicting tumor malignancy. The aim in management is to balance the utility of performing a biopsy and the appropriateness of upfront surgery against the ultimate goal of decreasing overtreatment.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11369/445549
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