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Evaluation of anatomic and morphologic nomogram to predict malignant and high-grade disease in a cohort of patients with small renal masses

Aditya Bagrodia; Brian Harrow; Zhuo-Wei Liu; Ephrem O. Olweny; Stephen Faddegon; Gang Yin; Yung Khan Tan; Woong Kyu Han; Yair Lotan; Vitaly Margulis; et al.

(Profiled Authors: Jeffrey A Cadeddu; Yair Lotan; Vitaly Margulis)

Urologic Oncology: Seminars and Original Investigations. 2014;32(1):37.e17-37.e23.

Abstract

Objective: To evaluate a nomogram using the RENAL Nephrometry Score (RENAL-NS) that was developed to characterize masses as benign vs. malignant and high vs. low grade in our patients with small renal masses treated with partial nephrectomy (PN). The nomogram was previously developed and validated in patients with widely variable tumor sizes. Materials and methods: Retrospective review of PN performed between 1/2003 and 7/2011. Imaging was reviewed by a urologic surgeon for RENAL-NS. Final pathology was used to classify tumors as benign or malignant and low (I/II) or high (III/IV) Fuhrman grade. Patient age, gender, and RENAL score were entered into the nomogram described by Kutikov et al. to determine probabilities of cancer and high-grade disease. Area under the curve was determined to assess agreement between observed and expected outcomes for prediction of benign vs. malignant disease and for prediction of high- vs. low-grade or benign disease. Results: A total of 250 patients with 252 masses underwent PN during the study period; 179/250 (71.6%) had preoperative imaging available. RENAL-NS was assigned to 181 masses. Twenty-two percent of tumors were benign. Eighteen percent of tumors were high grade. Area under the curve was 0.648 for predicting benign vs. malignant disease and 0.955 for predicting low-grade or benign vs. high-grade disease. Conclusions: The RENAL-NS score nomogram by Kutikov does not discriminate well between benign and malignant disease for small renal masses. The nomogram may potentially be useful in identifying high-grade tumors. Further validation is required where the nomogram probability and final pathologic specimen are available. © 2014 Elsevier Inc.

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