Document Detail

Evaluation of Renal Mass Biopsy Risk Stratification Algorithm to Robotic Partial Nephrectomy: Could a Biopsy Have Guided Management?
MedLine Citation:
PMID:  24936720     Owner:  NLM     Status:  Publisher    
INTRODUCTION: We evaluated a published biopsy-directed small renal mass (SRM) management algorithm using a large cohort of patients who underwent robotic partial nephrectomy (RPN) for tumors ≤4cm in size.
METHODS: A simplified algorithm of biopsy-directed SRM management reported by Halverson et al., using risk stratified biopsies, was applied to 1175 RPN cases from 5 academic centers. A theoretical assumption was made of "perfect" biopsies that were feasible for all patients and had 100% concordance to final pathology. Pathology risk groups were benign, favorable, unfavorable and intermediate. The algorithm assigned favorable or intermediate <2cm tumors to active surveillance (AS) and unfavorable or intermediate 2-4cm tumors to treatment. Higher surgical risk patients were defined as ASA≥3 and age≥70.
RESULTS: Patients were assigned to the following pathology risk groups: benign-23%, favorable-13%, intermediate-51%, and unfavorable-12%. Patients were assigned to the following management groups: benign pathology-275(23%), AS-336(29%), and treatment-564(48%). Most of the 611(52%) patients in the benign or AS groups were low surgical risk and had safe treatment (2.6% high grade complications). A biopsy may not have been feasible or accurate in some tumors that were anterior-378(32%), hilar-93(7.9%), or <2cm-379(32%). For 129(11%) high surgical risk patients, the biopsy algorithm assigned 70(54%) to benign or AS groups.
CONCLUSIONS: The theoretical application of a biopsy-driven risk-stratified SRM management algorithm to a large RPN database suggests that about half of patients might have avoided surgery. Despite obvious limitations of a theoretical assumption of all patients receiving a perfect biopsy, the data supports the emerging role for renal mass biopsies to guide management, particularly in high risk surgical patients .
Haider Rahbar; Sam Bhayani; Michael Stifelman; Jihad Kaouk; Mohamad Allaf; Susan Marshall; Homayoun Zargar; Mark Ball; Jeffrey Larson; Craig Rogers
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2014-6-14
Journal Detail:
Title:  The Journal of urology     Volume:  -     ISSN:  1527-3792     ISO Abbreviation:  J. Urol.     Publication Date:  2014 Jun 
Date Detail:
Created Date:  2014-6-17     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0376374     Medline TA:  J Urol     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2014 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
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