Preoperative differentiation between benign and malignant renal masses smaller than 4 cm treated with partial nephrectomy - Abstract

BACKGROUND: The aim of this study is to accurately differentiate between benign and malignant small renal masses (SRMs) prior to surgery.

METHODS: The study included 144 patients with SRMs < 4 cm suspected to be renal cell carcinoma (RCC) based on several imaging examinations, who subsequently underwent partial nephrectomy. Clinicopathological data were analyzed based on the preoperative findings obtained from enhanced computed tomography (CT) as follows: group 1 showing a typical imaging pattern for clear cell RCC (CCRCC), and group 2 showing an imaging pattern atypical of CCRCC. We then evaluated the association between clinicopathological characteristics and pathological diagnosis in order to identify factors which can predict the pathological diagnosis.

RESULTS: Based on the criteria, 102 (70.8 %) and 42 (29.2 %) patients were classified into group 1 and group 2, respectively. The only independent factor identified to predict the final pathological diagnosis of the 144 patients was preoperative CT findings. Only 7 (6.9 %) patients were pathologically diagnosed with benign tumors in group 1; however, 13 (31.0 %) of the 42 patients in group 2 appeared to have pathologically confirmed benign tumors. A younger age and lower body mass index (BMI) in group 2 were shown to be independently associated with benign histology on multivariate analysis.

CONCLUSIONS: The proportion of patients with benign tumors was comparatively high in those with CT findings atypical for CCRCC; therefore, other clinical parameters, such as age and BMI, should be considered when determining therapeutic strategies for patients with such SRMs.

Written by:
Nishikawa M, Miyake H, Kitajima K, Takahashi S, Sugimura K, Fujisawa M.   Are you the author?
Division of Urology, Kobe University Graduate School of Medicine, 7-5-1 Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.

Reference: Int J Clin Oncol. 2014 Feb 15. Epub ahead of print.
doi: 10.1007/s10147-014-0673-7


PubMed Abstract
PMID: 24526391

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