Rates and Predictors of Perioperative Complications in Cytoreductive Nephrectomy: Analysis of the Registry for Metastatic Renal Cell Carcinoma.


Journal

European urology oncology
ISSN: 2588-9311
Titre abrégé: Eur Urol Oncol
Pays: Netherlands
ID NLM: 101724904

Informations de publication

Date de publication:
08 2020
Historique:
received: 27 02 2020
revised: 13 04 2020
accepted: 22 04 2020
pubmed: 18 5 2020
medline: 1 6 2021
entrez: 17 5 2020
Statut: ppublish

Résumé

Cytoreductive nephrectomy (CN) plays an important role in the treatment of a subgroup of metastatic renal cell carcinoma (mRCC) patients. We aimed to evaluate morbidity associated with this procedure and identify potential predictors thereof to aid patient selection for this procedure and potentially improve patient outcomes. Data from 736 mRCC patients undergoing CN at 14 institutions were retrospectively recorded in the Registry for Metastatic RCC (REMARCC). Logistic regression analysis was used to identify predictors for intraoperative, any-grade (AGCs), low-grade, and high-grade (HGCs) postoperative complications (according to the Clavien-Dindo classification) as well as 30-d readmission rates. Intraoperative complications were observed in 69 patients (10.9%). Thrombectomy (odds ratio [OR] 1.38, 95% confidence interval [CI] 1.08-1.75, p = 0.009) and adjacent organ removal (OR 2.7, 95% CI 1.38-5.30) were significant predictors of intraoperative complications at multivariable analysis. Two hundred seventeen patients (29.5%) encountered AGCs, while 45 (6.1%) encountered an HGC, of whom 10 (1.4%) died. Twenty-four (3.3%) patients had multiple postoperative complications. Estimated blood loss (EBL; OR 1.49, 95% CI 1.08-2.05, p = 0.01) was a significant predictor of AGCs at multivariable analysis. CN case load (OR 0.13, 95% CI 0.03-0.59, p = 0.009) and EBL (OR 2.93, 95% CI 1.20-7.15, p = 0.02) were significant predictors solely for HGCs at multivariable analysis. Forty-one patients (11.5%) were readmitted within 30 d of surgery. No significant predictors were identified. Results were confirmed in a subanalysis focusing solely on patients treated in the contemporary targeted therapy era. Morbidity associated with CN is not negligible. Predictors of high-grade postoperative morbidity are predominantly indicators of complex surgery. EBL is a strong predictor of postoperative complications. CN case load correlates with lower high-grade morbidity and highlights the benefit of centralization of complex surgery. However, risks and benefits should be balanced when considering CN in mRCC patients. We studied patients with metastatic renal cancer to evaluate the outcomes associated with the surgical removal of the primary kidney tumor. We found that this procedure is often complex and adverse events are not uncommon. High intraoperative blood loss and a small number of cases performed at the treating center are associated with a higher rate of postoperative complications.

Sections du résumé

BACKGROUND
Cytoreductive nephrectomy (CN) plays an important role in the treatment of a subgroup of metastatic renal cell carcinoma (mRCC) patients.
OBJECTIVE
We aimed to evaluate morbidity associated with this procedure and identify potential predictors thereof to aid patient selection for this procedure and potentially improve patient outcomes.
DESIGN, SETTING, AND PARTICIPANTS
Data from 736 mRCC patients undergoing CN at 14 institutions were retrospectively recorded in the Registry for Metastatic RCC (REMARCC).
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS
Logistic regression analysis was used to identify predictors for intraoperative, any-grade (AGCs), low-grade, and high-grade (HGCs) postoperative complications (according to the Clavien-Dindo classification) as well as 30-d readmission rates.
RESULTS AND LIMITATIONS
Intraoperative complications were observed in 69 patients (10.9%). Thrombectomy (odds ratio [OR] 1.38, 95% confidence interval [CI] 1.08-1.75, p = 0.009) and adjacent organ removal (OR 2.7, 95% CI 1.38-5.30) were significant predictors of intraoperative complications at multivariable analysis. Two hundred seventeen patients (29.5%) encountered AGCs, while 45 (6.1%) encountered an HGC, of whom 10 (1.4%) died. Twenty-four (3.3%) patients had multiple postoperative complications. Estimated blood loss (EBL; OR 1.49, 95% CI 1.08-2.05, p = 0.01) was a significant predictor of AGCs at multivariable analysis. CN case load (OR 0.13, 95% CI 0.03-0.59, p = 0.009) and EBL (OR 2.93, 95% CI 1.20-7.15, p = 0.02) were significant predictors solely for HGCs at multivariable analysis. Forty-one patients (11.5%) were readmitted within 30 d of surgery. No significant predictors were identified. Results were confirmed in a subanalysis focusing solely on patients treated in the contemporary targeted therapy era.
CONCLUSIONS
Morbidity associated with CN is not negligible. Predictors of high-grade postoperative morbidity are predominantly indicators of complex surgery. EBL is a strong predictor of postoperative complications. CN case load correlates with lower high-grade morbidity and highlights the benefit of centralization of complex surgery. However, risks and benefits should be balanced when considering CN in mRCC patients.
PATIENT SUMMARY
We studied patients with metastatic renal cancer to evaluate the outcomes associated with the surgical removal of the primary kidney tumor. We found that this procedure is often complex and adverse events are not uncommon. High intraoperative blood loss and a small number of cases performed at the treating center are associated with a higher rate of postoperative complications.

Identifiants

pubmed: 32414697
pii: S2588-9311(20)30054-7
doi: 10.1016/j.euo.2020.04.006
pii:
doi:

Types de publication

Journal Article Multicenter Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

523-529

Informations de copyright

Copyright © 2020. Published by Elsevier B.V.

Auteurs

Eduard Roussel (E)

Department of Urology, University Hospitals Leuven, Leuven, Belgium.

Riccardo Campi (R)

Department of Urology, University of Florence, Careggi Hospital, Florence, Italy; Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.

Alessandro Larcher (A)

Department of Urology, San Raffaele Scientific Institute, Milan, Italy.

Annelies Verbiest (A)

Department of Medical Oncology, University Hospitals Leuven, Leuven, Belgium.

Alessandro Antonelli (A)

Department of Urology, Spedali Civili Hospital, University of Brescia, Brescia, Italy.

Carlotta Palumbo (C)

Department of Urology, Spedali Civili Hospital, University of Brescia, Brescia, Italy.

Ithaar Derweesh (I)

Department of Urology, University of California San Diego Cancer Center, Lousiana Jolla, CA, USA.

Fady Ghali (F)

Department of Urology, University of California San Diego Cancer Center, Lousiana Jolla, CA, USA.

Aaron Bradshaw (A)

Department of Urology, University of California San Diego Cancer Center, Lousiana Jolla, CA, USA.

Margaret F Meagher (MF)

Department of Urology, University of California San Diego Cancer Center, Lousiana Jolla, CA, USA.

Matthias Heck (M)

Department of Urology, Technical University of Munich, Munich, Germany.

Thomas Amiel (T)

Department of Urology, Technical University of Munich, Munich, Germany.

Maximilian C Kriegmair (MC)

Department of Urology, University Medical Centre Mannheim, Mannheim, Germany.

Jose Rubio (J)

Department of Urology, Fundacion Instituto Valenciano Oncologia, Valencia, Spain.

Mireia Musquera (M)

Department of Urology, Hospital Clinic, Barcelona, Spain.

Maurizio D'Anna (M)

Department of Urology, Hospital Clinic, Barcelona, Spain.

Riccardo Autorino (R)

Department of Urology, VCU Medical Center, Richmond, VA, USA.

Georgi Guruli (G)

Department of Urology, VCU Medical Center, Richmond, VA, USA.

Alessandro Veccia (A)

Department of Urology, VCU Medical Center, Richmond, VA, USA.

Estefania Linares-Espinos (E)

Department of Urology, Hospital La Paz, Madrid, Spain.

Siska Van Bruwaene (S)

Department of Urology, AZ Groeninge, Kortrijk, Belgium.

Vital Hevia (V)

Department of Urology, Hospital Ramon y Cajal, Madrid, Spain.

Francesco Porpiglia (F)

Department of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy.

Enrico Checcucci (E)

Department of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy.

Andrea Minervini (A)

Department of Urology, University of Florence, Careggi Hospital, Florence, Italy; Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.

Andrea Mari (A)

Department of Urology, University of Florence, Careggi Hospital, Florence, Italy; Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.

Nicola Pavan (N)

Urology Clinic, Department of Medical, Surgical and Health Science, University of Trieste, Trieste, Italy.

Francesco Claps (F)

Department of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy.

Michele Marchioni (M)

Department of Medical, Oral and Biotechnological Sciences, Laboratory of Biostatistics, "G. d'Annunzio" University of Chieti, Chieti, Italy; Department of Urology, SS Annunziata Hospital, "G. D'Annunzio" University of Chieti, Chieti, Italy.

Umberto Capitanio (U)

Department of Urology, San Raffaele Scientific Institute, Milan, Italy.

Benoit Beuselinck (B)

Department of Medical Oncology, University Hospitals Leuven, Leuven, Belgium.

Maria C Mir (MC)

Department of Urology, Fundacion Instituto Valenciano Oncologia, Valencia, Spain. Electronic address: mirmare@yahoo.es.

Maarten Albersen (M)

Department of Urology, University Hospitals Leuven, Leuven, Belgium.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH