Excision Versus Ablation in Renal Cancer: Optimising Outcome and Minimising Risk.

Abstract

In this month’s issue of European Urology, Larcher et al [1] have proposed an approach for stratification of complication risk after partial nephrectomy (PN) or local tumour ablation (LTA) for organ-confined renal cancer, in an effort to optimise clinical decision making, particularly in higher risk patents. Specifically, they aimed to identify patients who would more likely benefit from LTA rather than PN. They concluded that patients at high risk of complications from PN may benefit the most from LTA and may represent ideal LTA candidates. The authors undertook a population-based assessment of 2476 patients in the US Surveillance Epidemiology and End Results (SEER)–Medicare database who had clinical stage T1a kidney cancer treated with either LTA or PN between 2000 and 2009, and they raise some interesting points on the basis of their subsequent analysis. The authors acknowledge some limitations in the data. Only 514 (21%) of patients in this unrandomised cohort underwent LTA, with PN being the predominant treatment modality. The SEER database was described as identifying ‘‘28% of all cancer cases,’’ which clearly may invoke major data submission bias. In addition, the patients undergoing PN tended to be younger, healthier, and more free from preexisting renal impairment; had smaller tumours; and were more often diagnosed with a specific renal cell carcinoma subtype (likely testifying to more ‘‘corticated,’’ surgically accessible disease). It seems likely that the nonrandomised preselection of patients would have a significant impact on the expected complication profile of either technique. In particular, the analysis seemed insensitive to the numbers of patients with solitary

DOI: 10.1016/j.eururo.2015.10.004

Cite this paper

@article{Hayes2016ExcisionVA, title={Excision Versus Ablation in Renal Cancer: Optimising Outcome and Minimising Risk.}, author={Matthew C. Hayes and David J. K. Breen}, journal={European urology}, year={2016}, volume={69 4}, pages={683-4} }