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Trends in the Use of Nephron-Sparing Surgery over 7 Years: An Analysis Using the R.E.N.A.L. Nephrometry Scoring System
Authors:Seung Jea Shin  Kwang Jin Ko  Tae Sun Kim  Hyun Soo Ryoo  Hyun Hwan Sung  Hwang Gyun Jeon  Byong Chang Jeong  Seong Il Seo  Hyun Moo Lee  Han Yong Choi  Seong Soo Jeon
Institution:Department of Urology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.; Sun Yat-sen University, CHINA,
Abstract:

Objective

To analyze trends in the use of partial nephrectomy, we evaluated which individual factors of renal nephrometry score (RNS) influenced the operative approach bi-annually from 2008 to 2014.

Materials and Methods

We performed a retrospective review of renal cell carcinoma treated by surgery in 2008, 2010, 2012, and 2014. The complexity of renal masses was measured using the R.E.N.A.L. nephrometry scoring system with CT or MRI. Group comparison in terms of operation year and surgical type (partial nephrectomy versus radical nephrectomy) was performed. We developed a nomogram to quantitate the likelihood of selecting partial nephrectomy over radical nephrectomy.

Results

A total of 1106 cases (237 in 2008, 225 in 2010, 292 in 2012, and 352 in 2014) were available for the study. Over the study period, the proportion of partial nephrectomies performed increased steadily from 21.5% in 2008 to 66.5% in 2014 (p < 0.05). Furthermore, use of partial nephrectomy increased steadily in all RNS complexity groups (low, moderate, and high) (p < 0.05). In the analysis of individual components of RNS, values of the R and N components increased statistically by year in the partial nephrectomy group (p < 0.05). Average AUC was 0.920.

Conclusions

The proportion of partial nephrectomies performed sharply increased over the study period. Additionally, over the study period, more partial nephrectomies were performed for renal masses of larger size and closer to the collecting system and main renal vessels. A nomogram developed based on this recent data set provides significant predictive value for surgical decision making.
Keywords:
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