PURPOSE: For patients with renal masses localized to the kidney there is currently no preoperative tool to predict the likelihood of metastatic recurrence following surgical intervention. We developed a predictive model that could be used in the preoperative setting. MATERIALS AND METHODS: We pooled institutional databases from Memorial Sloan-Kettering and Mayo Clinic, and identified complete data on 2,517 patients with renal masses and no concurrent evidence of metastases who underwent radical or partial nephrectomy. Cox proportional hazard regression analyses were used to model preoperative clinical and radiographic characteristics as predictors for development of metastases following nephrectomy. Internal validation was performed with a statistical bootstrapping technique. RESULTS: Metastatic recurrence developed in 340 of the 2,517 patients. Median followup for patients without metastatic recurrence was 4.7 years. A nomogram was developed using preoperative characteristics to predict the 12-year likelihood of postoperative metastatic recurrence with a concordance index of 0.80. In contrast, the concordance index of preoperative TNM staging was 0.71. Size of the primary renal mass, evidence of lymphadenopathy or necrosis on preoperative imaging and the mode of presentation were important predictors for the subsequent development of metastases. CONCLUSIONS: We present a preoperative nomogram that accurately predicts the development of metastatic recurrence following nephrectomy. This nomogram may be potentially useful to identify and counsel patients at high risk for recurrence.
PURPOSE: For patients with renal masses localized to the kidney there is currently no preoperative tool to predict the likelihood of metastatic recurrence following surgical intervention. We developed a predictive model that could be used in the preoperative setting. MATERIALS AND METHODS: We pooled institutional databases from Memorial Sloan-Kettering and Mayo Clinic, and identified complete data on 2,517 patients with renal masses and no concurrent evidence of metastases who underwent radical or partial nephrectomy. Cox proportional hazard regression analyses were used to model preoperative clinical and radiographic characteristics as predictors for development of metastases following nephrectomy. Internal validation was performed with a statistical bootstrapping technique. RESULTS: Metastatic recurrence developed in 340 of the 2,517 patients. Median followup for patients without metastatic recurrence was 4.7 years. A nomogram was developed using preoperative characteristics to predict the 12-year likelihood of postoperative metastatic recurrence with a concordance index of 0.80. In contrast, the concordance index of preoperative TNM staging was 0.71. Size of the primary renal mass, evidence of lymphadenopathy or necrosis on preoperative imaging and the mode of presentation were important predictors for the subsequent development of metastases. CONCLUSIONS: We present a preoperative nomogram that accurately predicts the development of metastatic recurrence following nephrectomy. This nomogram may be potentially useful to identify and counsel patients at high risk for recurrence.
Authors: Luca Cindolo; Jean-Jacques Patard; Paolo Chiodini; Luigi Schips; Vincenzo Ficarra; Jacques Tostain; Alexandre de La Taille; Vincenzo Altieri; Bernard Lobel; Richard E Zigeuner; Walter Artibani; François Guillé; Claude C Abbou; Luigi Salzano; Ciro Gallo Journal: Cancer Date: 2005-10-01 Impact factor: 6.860
Authors: John S Lam; Oleg Shvarts; John T Leppert; Allan J Pantuck; Robert A Figlin; Arie S Belldegrun Journal: J Urol Date: 2005-08 Impact factor: 7.450
Authors: Sam N Chawla; Paul L Crispen; Alexandra L Hanlon; Richard E Greenberg; David Y T Chen; Robert G Uzzo Journal: J Urol Date: 2006-02 Impact factor: 7.450
Authors: Michael J Wehle; David D Thiel; Steven P Petrou; Paul R Young; Igor Frank; Nolan Karsteadt Journal: Urology Date: 2004-07 Impact factor: 2.649
Authors: W Marston Linehan; James Vasselli; Ramaprasad Srinivasan; McClellan M Walther; Maria Merino; Peter Choyke; Cathy Vocke; Laura Schmidt; Jennifer S Isaacs; Gladys Glenn; Jorge Toro; Berton Zbar; Donald Bottaro; Len Neckers Journal: Clin Cancer Res Date: 2004-09-15 Impact factor: 12.531
Authors: Igor Frank; Michael L Blute; John C Cheville; Christine M Lohse; Amy L Weaver; Horst Zincke Journal: J Urol Date: 2002-12 Impact factor: 7.450
Authors: Gal Wald; Kerri T Barnes; Megan T Bing; Timothy P Kresowik; Ann Tomanek-Chalkley; Tamara A Kucaba; Thomas S Griffith; James A Brown; Lyse A Norian Journal: Urol Oncol Date: 2014-04-24 Impact factor: 3.498
Authors: Antoni Vilaseca; Daniel P Nguyen; Emily A Vertosick; Renato B Corradi; Mireia Musquera; Meritxell Pérez; Nicola Fossati; Daniel D Sjoberg; Ramon Farré; Isaac Almendros; Josep M Montserrat; Nicole E Benfante; A Ari Hakimi; Anders J Skanderup; Paul Russo; Antonio Alcaraz; Karim A Touijer Journal: World J Urol Date: 2016-04-23 Impact factor: 4.226
Authors: Christoph A Karlo; Lei Kou; Pier Luigi Di Paolo; Michael W Kattan; Robert J Motzer; Paul Russo; Satish K Tickoo; Oguz Akin; Hedvig Hricak Journal: Eur J Cancer Date: 2016-03-24 Impact factor: 9.162
Authors: S L Wood; M Rogers; D A Cairns; A Paul; D Thompson; N S Vasudev; P J Selby; R E Banks Journal: Br J Cancer Date: 2010-06-08 Impact factor: 7.640
Authors: Hebert Alberto Vargas; Holly G Delaney; Eithne M Delappe; Ya Wang; Junting Zheng; Chaya S Moskowitz; Yongqiang Tan; Binsheng Zhao; Lawrence H Schwartz; Hedvig Hricak; Paul Russo; Oguz Akin Journal: J Magn Reson Imaging Date: 2012-11-13 Impact factor: 4.813
Authors: N S Vasudev; S Sim; D A Cairns; R E Ferguson; R A Craven; A Stanley; J Cartledge; D Thompson; P J Selby; R E Banks Journal: Br J Cancer Date: 2009-10-06 Impact factor: 7.640