OBJECTIVE: The goal of anatomical classification systems (ACSs) is to assess renal tumour complexity and predict surgical complications. However, the present ACSs may include some relatively unimportant components and may be complicated to use. This study introduces the invasion depth of the renal tumour divided by the parenchymal thickness, called the renal tumour invasion index (RTII), as a novel ACS and compares it with previous ACSs in predicting urological complications after partial nephrectomy. MATERIAL AND METHODS: This retrospective single-institution study assessed 280 consecutive patients subjected to a planned partial nephrectomy. The main outcome was perioperative 30-day urological complications. RTII was compared with the PADUA (preoperative aspects and dimensions used for an anatomical) classification score, RENAL (radius, exophytic/endophytic, nearness to collecting system or sinus, anterior/posterior and location relative to polar lines) nephrometry score and C (centrality) index to predict urological complications, using statistical methods of receiver operating curve and logistic binary regression. RESULTS: Areas under the curve for RTII, RENAL, C index and PADUA were 0.64 (95% CI 0.57-0.72, p < 0.001), 0.61 (95% CI 0.54-0.69, p = 0.004), 0.64 (95% CI 0.57-0.71, p < 0.001) and 0.57 (95% CI 0.49-0.65, p = 0.06), respectively, indicating that all the ACSs studied are able to predict urological complications. Similarly, in a multivariate logistic regression model adjusted for comorbidity and surgical approach, all ACSs were statistically significant predictors of urological complications. CONCLUSIONS: RTII is as good as the previous more complicated ACSs in predicting urological complications after partial nephrectomy. As a simple measurement with a straightforward anatomical interpretation, RTII may be useful in counselling patients and stratifying patients in studies.
OBJECTIVE: The goal of anatomical classification systems (ACSs) is to assess renal tumour complexity and predict surgical complications. However, the present ACSs may include some relatively unimportant components and may be complicated to use. This study introduces the invasion depth of the renal tumour divided by the parenchymal thickness, called the renal tumour invasion index (RTII), as a novel ACS and compares it with previous ACSs in predicting urological complications after partial nephrectomy. MATERIAL AND METHODS: This retrospective single-institution study assessed 280 consecutive patients subjected to a planned partial nephrectomy. The main outcome was perioperative 30-day urological complications. RTII was compared with the PADUA (preoperative aspects and dimensions used for an anatomical) classification score, RENAL (radius, exophytic/endophytic, nearness to collecting system or sinus, anterior/posterior and location relative to polar lines) nephrometry score and C (centrality) index to predict urological complications, using statistical methods of receiver operating curve and logistic binary regression. RESULTS: Areas under the curve for RTII, RENAL, C index and PADUA were 0.64 (95% CI 0.57-0.72, p < 0.001), 0.61 (95% CI 0.54-0.69, p = 0.004), 0.64 (95% CI 0.57-0.71, p < 0.001) and 0.57 (95% CI 0.49-0.65, p = 0.06), respectively, indicating that all the ACSs studied are able to predict urological complications. Similarly, in a multivariate logistic regression model adjusted for comorbidity and surgical approach, all ACSs were statistically significant predictors of urological complications. CONCLUSIONS: RTII is as good as the previous more complicated ACSs in predicting urological complications after partial nephrectomy. As a simple measurement with a straightforward anatomical interpretation, RTII may be useful in counselling patients and stratifying patients in studies.
Authors: Darren Desantis; Luke T Lavallée; Kelsey Witiuk; Ranjeeta Mallick; Fadi Kamal; Dean Fergusson; Christopher Morash; Ilias Cagiannos; Rodney H Breau Journal: Can Urol Assoc J Date: 2015 Jan-Feb Impact factor: 1.862
Authors: Luke T Lavallée; Simon Tanguay; Michael A Jewett; Lori Wood; Anil Kapoor; Ricardo A Rendon; Ronald B Moore; Louis Lacombe; Jun Kawakami; Stephen E Pautler; Darrel E Drachenberg; Peter C Black; Jean-Baptiste Lattouf; Christopher Morash; Ilias Cagiannos; Zhihui Liu; Rodney H Breau Journal: Can Urol Assoc J Date: 2015 Mar-Apr Impact factor: 1.862
Authors: Ricardo B Fonseca; Melissa M Straub Hogan; Meghan E Kapp; Frances Cate; Alice Coogan; Sandeep Arora; Jennifer Gordetsky; Woodson W Smelser; Peter E Clark; Justin Cates; Giovanna A Giannico Journal: Urol Oncol Date: 2021-03-26 Impact factor: 2.954
Authors: X F Li; Y J Peng; X T Yu; S W Xiong; S D Cheng; G P Ding; K L Yang; Q Tang; Y Mi; J Y Wu; P Zhang; J X Xie; H Hao; H Wang; J X Qiu; J Yang; X S Li; L Q Zhou Journal: Beijing Da Xue Xue Bao Yi Xue Ban Date: 2021-06-18