Background: Postoperative renal function impairment represents a main limitation for delivering adjuvant chemotherapy after radical nephroureterectomy (RNU).Objective: To create a model predicting renal function decline after minimally invasive RNU.Design, setting, and participants: A total of 490 patients with nonmetastatic UTUC who underwent minimally invasive RNU were identified from a collaborative database including 17 institutions worldwide (February 2006 to March 2020). Renal function insufficiency for cisplatin-based regimen was defined as estimated glomerular filtration rate (eGFR) <50 ml/min/1.73 m(2) at 3 mo after RNU. Patients with baseline eGFR >50 ml/ min/1.73 m2 (n = 361) were geographically divided into a training set (n = 226) and an independent external validation set (n = 135) for further analysis.Outcome measurements and statistical analysis: Using transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guidelines, a nomogram to predict postoperative eGFR <50 ml/min/1.73 m(2) was built based on the coefficients of the least absolute shrinkage and selection operation (LASSO) logistic regression. The discrimination, calibration, and clinical use of the nomogram were investigated.Results and limitations: The model that incorporated age, body mass index, preoperative eGFR, and hydroureteronephrosis was developed with an area under the curve of 0.771, which was confirmed to be 0.773 in the external validation set. The calibration curve demonstrated good agreement. Besides, the model was converted into a risk score with a cutoff value of 0.583, and the difference between the low-and high-risk groups both in overall death risk (hazard ratio [HR]: 4.59, p < 0.001) and cancer-specific death risk (HR: 5.19, p < 0.001) was statistically significant. The limitation mainly lies in its retrospective design.Conclusions: A nomogram incorporating immediately available clinical variables can accurately predict renal insufficiency for cisplatin-based adjuvant chemotherapy after minimally invasive RNU and may serve as a tool facilitating patient selection.Patient summary: We have developed a model for the prediction of renal function loss after radical nephroureterectomy to facilitate patient selection for perioperative chemotherapy. (C) 2021 European Association of Urology. Published by Elsevier B.V. All rights reserved.

A Preoperative Nomogram to Predict Renal Function Insufficiency for Cisplatin-based Adjuvant Chemotherapy Following Minimally Invasive Radical Nephroureterectomy (ROBUUST Collaborative Group) / Wu, Zhenjie; Chen, Qi; Djaladat, Hooman; Minervini, Andrea; Uzzo, Robert G; Sundaram, Chandru P; Rha, Koon H; Gonzalgo, Mark L; Mehrazin, Reza; Mazzone, Elio; Marcus, Jamil; Danno, Alyssa; Porter, James; Asghar, Aeen; Ghali, Fady; Guruli, Georgi; Douglawi, Antoin; Cacciamani, Giovanni; Ghoreifi, Alireza; Simone, Giuseppe; Margulis, Vitaly; Ferro, Matteo; Tellini, Riccardo; Mari, Andrea; Srivastava, Abhishek; Steward, James; Al-Qathani, Ali; Al-Mujalhem, Ahmad; Bhattu, Amit Satish; Mottrie, Alexander; Abdollah, Firas; Eun, Daniel D; Derweesh, Ithaar; Veccia, Alessandro; Autorino, Riccardo; Wang, Linhui. - In: EUROPEAN UROLOGY FOCUS. - ISSN 2405-4569. - ELETTRONICO. - 8:(2022), pp. 173-181. [10.1016/j.euf.2021.01.014]

A Preoperative Nomogram to Predict Renal Function Insufficiency for Cisplatin-based Adjuvant Chemotherapy Following Minimally Invasive Radical Nephroureterectomy (ROBUUST Collaborative Group)

Minervini, Andrea;Tellini, Riccardo;Mari, Andrea;
2022

Abstract

Background: Postoperative renal function impairment represents a main limitation for delivering adjuvant chemotherapy after radical nephroureterectomy (RNU).Objective: To create a model predicting renal function decline after minimally invasive RNU.Design, setting, and participants: A total of 490 patients with nonmetastatic UTUC who underwent minimally invasive RNU were identified from a collaborative database including 17 institutions worldwide (February 2006 to March 2020). Renal function insufficiency for cisplatin-based regimen was defined as estimated glomerular filtration rate (eGFR) <50 ml/min/1.73 m(2) at 3 mo after RNU. Patients with baseline eGFR >50 ml/ min/1.73 m2 (n = 361) were geographically divided into a training set (n = 226) and an independent external validation set (n = 135) for further analysis.Outcome measurements and statistical analysis: Using transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guidelines, a nomogram to predict postoperative eGFR <50 ml/min/1.73 m(2) was built based on the coefficients of the least absolute shrinkage and selection operation (LASSO) logistic regression. The discrimination, calibration, and clinical use of the nomogram were investigated.Results and limitations: The model that incorporated age, body mass index, preoperative eGFR, and hydroureteronephrosis was developed with an area under the curve of 0.771, which was confirmed to be 0.773 in the external validation set. The calibration curve demonstrated good agreement. Besides, the model was converted into a risk score with a cutoff value of 0.583, and the difference between the low-and high-risk groups both in overall death risk (hazard ratio [HR]: 4.59, p < 0.001) and cancer-specific death risk (HR: 5.19, p < 0.001) was statistically significant. The limitation mainly lies in its retrospective design.Conclusions: A nomogram incorporating immediately available clinical variables can accurately predict renal insufficiency for cisplatin-based adjuvant chemotherapy after minimally invasive RNU and may serve as a tool facilitating patient selection.Patient summary: We have developed a model for the prediction of renal function loss after radical nephroureterectomy to facilitate patient selection for perioperative chemotherapy. (C) 2021 European Association of Urology. Published by Elsevier B.V. All rights reserved.
2022
8
173
181
Wu, Zhenjie; Chen, Qi; Djaladat, Hooman; Minervini, Andrea; Uzzo, Robert G; Sundaram, Chandru P; Rha, Koon H; Gonzalgo, Mark L; Mehrazin, Reza; Mazzon...espandi
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1287808
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