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

Chemotherapy, Adjuvant Cisplatin / therapeutic use Humans Kidney / physiology Nephrectomy / methods Nephroureterectomy Nomograms Retrospective Studies
Chemotherapy Functional outcome Radical nephroureterectomy Upper tract urinary carcinoma

Journal

European urology focus
ISSN: 2405-4569
Titre abrégé: Eur Urol Focus
Pays: Netherlands
ID NLM: 101665661

Informations de publication

Date de publication:
Jan 2022
Historique:
received: 26 10 2020
revised: 16 12 2020
accepted: 13 01 2021
pubmed: 8 2 2021
medline: 15 4 2022
entrez: 7 2 2021
Statut: ppublish

Résumé

Postoperative renal function impairment represents a main limitation for delivering adjuvant chemotherapy after radical nephroureterectomy (RNU). To create a model predicting renal function decline after minimally invasive RNU. 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 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 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. 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. We have developed a model for the prediction of renal function loss after radical nephroureterectomy to facilitate patient selection for perioperative chemotherapy.

Sections du résumé

BACKGROUND BACKGROUND
Postoperative renal function impairment represents a main limitation for delivering adjuvant chemotherapy after radical nephroureterectomy (RNU).
OBJECTIVE OBJECTIVE
To create a model predicting renal function decline after minimally invasive RNU.
DESIGN, SETTING, AND PARTICIPANTS METHODS
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
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS METHODS
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
RESULTS AND LIMITATIONS CONCLUSIONS
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 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 RESULTS
We have developed a model for the prediction of renal function loss after radical nephroureterectomy to facilitate patient selection for perioperative chemotherapy.

Identifiants

DOI: 10.1016/j.euf.2021.01.014 PMID: 33549537
pubmed: 33549537
pii: S2405-4569(21)00015-8
doi: 10.1016/j.euf.2021.01.014
pii:
doi:

Substances chimiques

Cisplatin Q20Q21Q62J

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

173-181

Commentaires et corrections

Type : ErratumIn

Informations de copyright

Copyright © 2021 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Auteurs

Zhenjie Wu (Z)

Department of Urology, Changzheng Hospital, Naval Medical University, Shanghai, China.

Qi Chen (Q)

Department of Health Statistics, Naval Medical University, Shanghai, China.

Hooman Djaladat (H)

Institute of Urology & Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.

Andrea Minervini (A)

Department of Experimental and Clinical Medicine, University of Florence - Unit of Oncologic Minimally-Invasive Urology and Andrology, Careggi Hospital, Florence, Italy.

Robert G Uzzo (RG)

Division of Urologic Oncology, Department of Surgical Oncology, Fox Chase Cancer Center, Philadelphia, PA, USA.

Chandru P Sundaram (CP)

Indiana University School of Medicine, Indianapolis, IN, USA.

Koon H Rha (KH)

Department of Urology, Urological Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea.

Mark L Gonzalgo (ML)

Department of Urology, University of Miami Miller School of Medicine, Miami, FL, USA.

Reza Mehrazin (R)

Icahn School of Medicine at Mount Sinai, Department of Urology, New York, NY, USA.

Elio Mazzone (E)

OLV Hospital, Aalst, Belgium;ORSI Academy, Melle, Belgium.

Jamil Marcus (J)

Vattikuti Urology Institute, Henry Ford Hospital, Detroit, MI, USA.

Alyssa Danno (A)

Vattikuti Urology Institute, Henry Ford Hospital, Detroit, MI, USA.

James Porter (J)

Swedish Medical Center, Seattle, WA, USA.

Aeen Asghar (A)

Department of Urology, Temple University, Philadelphia, PA, USA.

Fady Ghali (F)

Department of Urology, UCSD, San Diego, CA, USA.

Georgi Guruli (G)

Division of Urology, VCU Health, Richmond, VA, USA.

Antoin Douglawi (A)

Institute of Urology & Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.

Giovanni Cacciamani (G)

Institute of Urology & Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.

Alireza Ghoreifi (A)

Institute of Urology & Catherine and Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.

Giuseppe Simone (G)

Department of Urology, Regina Elena National Cancer Institute, Rome, Italy.

Vitaly Margulis (V)

Department of Urology, University of Texas Southwestern Medical Center, Dallas, TX, USA.

Matteo Ferro (M)

Division of Urology - European Institute of Oncology, IRCCS.

Riccardo Tellini (R)

Department of Experimental and Clinical Medicine, University of Florence - Unit of Oncologic Minimally-Invasive Urology and Andrology, Careggi Hospital, Florence, Italy.

Andrea Mari (A)

Department of Experimental and Clinical Medicine, University of Florence - Unit of Oncologic Minimally-Invasive Urology and Andrology, Careggi Hospital, Florence, Italy.

Abhishek Srivastava (A)

Division of Urologic Oncology, Department of Surgical Oncology, Fox Chase Cancer Center, Philadelphia, PA, USA.

James Steward (J)

Indiana University School of Medicine, Indianapolis, IN, USA.

Ali Al-Qathani (A)

Department of Urology, Urological Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea.

Ahmad Al-Mujalhem (A)

Department of Urology, Urological Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea.

Amit Satish Bhattu (AS)

Department of Urology, University of Miami Miller School of Medicine, Miami, FL, USA.

Alexander Mottrie (A)

OLV Hospital, Aalst, Belgium;ORSI Academy, Melle, Belgium.

Firas Abdollah (F)

Vattikuti Urology Institute, Henry Ford Hospital, Detroit, MI, USA.

Daniel D Eun (DD)

Department of Urology, Temple University, Philadelphia, PA, USA.

Ithaar Derweesh (I)

Department of Urology, UCSD, San Diego, CA, USA.

Alessandro Veccia (A)

Division of Urology, VCU Health, Richmond, VA, USA.

Riccardo Autorino (R)

Division of Urology, VCU Health, Richmond, VA, USA.

Linhui Wang (L)

Department of Urology, Changzheng Hospital, Naval Medical University, Shanghai, China. Electronic address: wanglinhui@smmu.edu.cn.

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