Takahiro Osawa1, Khaled S Hafez2, David C Miller2, Jeffrey S Montgomery2, Todd M Morgan2, Ganesh S Palapattu2, Alon Z Weizer2, Elaine M Caoili3, James H Ellis4, Lakshmi P Kunju5, J Stuart Wolf2. 1. Department of Urology, University of Michigan Health System, Ann Arbor, MI. Electronic address: taka0573@gmail.com. 2. Department of Urology, University of Michigan Health System, Ann Arbor, MI. 3. Department of Radiology, University of Michigan Health System, Ann Arbor, MI. 4. Department of Urology, University of Michigan Health System, Ann Arbor, MI; Department of Radiology, University of Michigan Health System, Ann Arbor, MI. 5. Department of Pathology, University of Michigan Health System, Ann Arbor, MI.
Abstract
OBJECTIVE: To compare the accuracies of renal mass biopsy (RMB) and R.E.N.A.L. nephrometry score (RNS) nomograms for predicting benign vs malignant disease, and low- vs high-risk renal tumors. MATERIALS AND METHODS: We included 281 renal masses in 277 patients who had complete RNS, preoperative RMB, and final pathology from renal surgery for clinically localized renal tumors. RMB and final pathology were determined to be benign or malignant, and malignancies were classified as low-risk (Fuhrman grade I/II) or high-risk (Fuhrman grade III/IV) (benign included in low-risk group). Previously published RNS nomograms were used to determine probabilities of any cancer and high-risk cancer. The gamma statistic was used to assess strength of association between RMB or RNS with final pathology. RESULTS: Of the 281 masses, 13 (5%) and 268 (95%) were confirmed benign and malignant, respectively, and 155 (55%) and 126 (45%) were confirmed low-risk and high-risk, respectively, on final pathology. The areas under the curve of the RNS nomograms for benign vs malignant disease and for low-risk vs high-risk renal tumors were 0.56 and 0.64, respectively. Concordances for predicting benign vs malignant disease were 99% for RMB (P < .01, gamma 0.99) and 29% for RNS nomogram (P = .16, gamma 0.38). Concordances for predicting low-risk vs high-risk renal tumors were 67% for RMB (P < .01, gamma 0.97) and 61% for RNS nomogram (P < .01, gamma 0.47), respectively. CONCLUSION: Although RNS nomograms are useful for discriminating between benign vs malignant renal masses, and low-risk vs high-risk renal tumors, they are outperformed by RMB.
OBJECTIVE: To compare the accuracies of renal mass biopsy (RMB) and R.E.N.A.L. nephrometry score (RNS) nomograms for predicting benign vs malignant disease, and low- vs high-risk renal tumors. MATERIALS AND METHODS: We included 281 renal masses in 277 patients who had complete RNS, preoperative RMB, and final pathology from renal surgery for clinically localized renal tumors. RMB and final pathology were determined to be benign or malignant, and malignancies were classified as low-risk (Fuhrman grade I/II) or high-risk (Fuhrman grade III/IV) (benign included in low-risk group). Previously published RNS nomograms were used to determine probabilities of any cancer and high-risk cancer. The gamma statistic was used to assess strength of association between RMB or RNS with final pathology. RESULTS: Of the 281 masses, 13 (5%) and 268 (95%) were confirmed benign and malignant, respectively, and 155 (55%) and 126 (45%) were confirmed low-risk and high-risk, respectively, on final pathology. The areas under the curve of the RNS nomograms for benign vs malignant disease and for low-risk vs high-risk renal tumors were 0.56 and 0.64, respectively. Concordances for predicting benign vs malignant disease were 99% for RMB (P < .01, gamma 0.99) and 29% for RNS nomogram (P = .16, gamma 0.38). Concordances for predicting low-risk vs high-risk renal tumors were 67% for RMB (P < .01, gamma 0.97) and 61% for RNS nomogram (P < .01, gamma 0.47), respectively. CONCLUSION: Although RNS nomograms are useful for discriminating between benign vs malignant renal masses, and low-risk vs high-risk renal tumors, they are outperformed by RMB.
Authors: Ran Sun; Sheng Zhao; Huijie Jiang; Hao Jiang; Yanmei Dai; Chuzhen Zhang; Song Wang Journal: Biomed Res Int Date: 2021-12-23 Impact factor: 3.411