When to perform lymph node dissection in patients with renal cell carcinoma: A novel approach to the preoperative assessment of risk of lymph node invasion at surgery and of lymph node progression during follow-up

Umberto Capitanio, Firas Abdollah, Rayan Matloob, Nazareno Suardi, Fabio Castiglione, Ettore Di Trapani, Paolo Capogrosso, Andrea Gallina, Paolo Dell'Oglio, Alberto Briganti, Andrea Salonia, Francesco Montorsi, Roberto Bertini

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Abstract

Objective To identify preoperatively patients who might benefit from lymph node dissection (LND). Patients and Methods We assessed lymph node invasion (LNI) at final pathology and lymph node (LN) progression during the follow-up for 1983 patients with RCC, treated with either partial or radical nephrectomy. LN progression was defined as the onset of a new clinically detected lymphadenopathy (>10 mm) in the retroperitoneal lymphatic area. Logistic regression analyses were used to assess the effect of each potential clinical predictor (age, body mass index, tumour side, symptoms, performance status, clinical tumour size, clinical tumour-node-metastasis stage, and albumin, calcium, creatinine, haemoglobin and platelet levels) on the outcome of interest. The most parsimonious multivariable predictive model was developed, and discrimination, calibration and net benefit were calculated. Results The prevalence of LNI was 6.1% (120/1983 patients) and during the follow-up period, 82 patients (4.1%) experienced LN progression. On multivariable analyses, the most informative independent predictors were tumour stage (cT3-4 vs cT1-2, odds ratio [OR] 1.52, P = 0.05), clinical nodal status [cN1 vs cN0, OR 7.09, P <0.001], metastases at diagnosis (OR 3.04, P <0.001) and clinical tumour size (OR 1.14, P <0.001). The accuracy of the multivariable model was found to be 86.9%, with excellent calibration and net benefit at decision-curve analyses. Conclusions By relying on a unique approach, combining the risk of harbouring LNI and/or LN progression during the follow-up period, we have provided the first clinical presurgery model predicting the need for LND.

Original languageEnglish
JournalBJU International
Volume112
Issue number2
DOIs
Publication statusPublished - Jul 2013

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Lymph Node Excision
Renal Cell Carcinoma
Lymph Nodes
Odds Ratio
Neoplasms
Calibration
Neoplasm Metastasis
Decision Support Techniques
Nephrectomy
Albumins
Creatinine
Hemoglobins
Body Mass Index
Blood Platelets
Logistic Models
Regression Analysis
Pathology
Calcium

Keywords

  • lymph node dissection
  • lymph node invasion
  • lymph node progression
  • lymphadenectomy
  • nomogram
  • RCC
  • renal cell carcinoma

ASJC Scopus subject areas

  • Urology

Cite this

@article{b9f88d45a797425381ec92b34e0ca5f4,
title = "When to perform lymph node dissection in patients with renal cell carcinoma: A novel approach to the preoperative assessment of risk of lymph node invasion at surgery and of lymph node progression during follow-up",
abstract = "Objective To identify preoperatively patients who might benefit from lymph node dissection (LND). Patients and Methods We assessed lymph node invasion (LNI) at final pathology and lymph node (LN) progression during the follow-up for 1983 patients with RCC, treated with either partial or radical nephrectomy. LN progression was defined as the onset of a new clinically detected lymphadenopathy (>10 mm) in the retroperitoneal lymphatic area. Logistic regression analyses were used to assess the effect of each potential clinical predictor (age, body mass index, tumour side, symptoms, performance status, clinical tumour size, clinical tumour-node-metastasis stage, and albumin, calcium, creatinine, haemoglobin and platelet levels) on the outcome of interest. The most parsimonious multivariable predictive model was developed, and discrimination, calibration and net benefit were calculated. Results The prevalence of LNI was 6.1{\%} (120/1983 patients) and during the follow-up period, 82 patients (4.1{\%}) experienced LN progression. On multivariable analyses, the most informative independent predictors were tumour stage (cT3-4 vs cT1-2, odds ratio [OR] 1.52, P = 0.05), clinical nodal status [cN1 vs cN0, OR 7.09, P <0.001], metastases at diagnosis (OR 3.04, P <0.001) and clinical tumour size (OR 1.14, P <0.001). The accuracy of the multivariable model was found to be 86.9{\%}, with excellent calibration and net benefit at decision-curve analyses. Conclusions By relying on a unique approach, combining the risk of harbouring LNI and/or LN progression during the follow-up period, we have provided the first clinical presurgery model predicting the need for LND.",
keywords = "lymph node dissection, lymph node invasion, lymph node progression, lymphadenectomy, nomogram, RCC, renal cell carcinoma",
author = "Umberto Capitanio and Firas Abdollah and Rayan Matloob and Nazareno Suardi and Fabio Castiglione and {Di Trapani}, Ettore and Paolo Capogrosso and Andrea Gallina and Paolo Dell'Oglio and Alberto Briganti and Andrea Salonia and Francesco Montorsi and Roberto Bertini",
year = "2013",
month = "7",
doi = "10.1111/bju.12125",
language = "English",
volume = "112",
journal = "BJU International",
issn = "1464-4096",
publisher = "Wiley-Blackwell Publishing Ltd",
number = "2",

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TY - JOUR

T1 - When to perform lymph node dissection in patients with renal cell carcinoma

T2 - A novel approach to the preoperative assessment of risk of lymph node invasion at surgery and of lymph node progression during follow-up

AU - Capitanio, Umberto

AU - Abdollah, Firas

AU - Matloob, Rayan

AU - Suardi, Nazareno

AU - Castiglione, Fabio

AU - Di Trapani, Ettore

AU - Capogrosso, Paolo

AU - Gallina, Andrea

AU - Dell'Oglio, Paolo

AU - Briganti, Alberto

AU - Salonia, Andrea

AU - Montorsi, Francesco

AU - Bertini, Roberto

PY - 2013/7

Y1 - 2013/7

N2 - Objective To identify preoperatively patients who might benefit from lymph node dissection (LND). Patients and Methods We assessed lymph node invasion (LNI) at final pathology and lymph node (LN) progression during the follow-up for 1983 patients with RCC, treated with either partial or radical nephrectomy. LN progression was defined as the onset of a new clinically detected lymphadenopathy (>10 mm) in the retroperitoneal lymphatic area. Logistic regression analyses were used to assess the effect of each potential clinical predictor (age, body mass index, tumour side, symptoms, performance status, clinical tumour size, clinical tumour-node-metastasis stage, and albumin, calcium, creatinine, haemoglobin and platelet levels) on the outcome of interest. The most parsimonious multivariable predictive model was developed, and discrimination, calibration and net benefit were calculated. Results The prevalence of LNI was 6.1% (120/1983 patients) and during the follow-up period, 82 patients (4.1%) experienced LN progression. On multivariable analyses, the most informative independent predictors were tumour stage (cT3-4 vs cT1-2, odds ratio [OR] 1.52, P = 0.05), clinical nodal status [cN1 vs cN0, OR 7.09, P <0.001], metastases at diagnosis (OR 3.04, P <0.001) and clinical tumour size (OR 1.14, P <0.001). The accuracy of the multivariable model was found to be 86.9%, with excellent calibration and net benefit at decision-curve analyses. Conclusions By relying on a unique approach, combining the risk of harbouring LNI and/or LN progression during the follow-up period, we have provided the first clinical presurgery model predicting the need for LND.

AB - Objective To identify preoperatively patients who might benefit from lymph node dissection (LND). Patients and Methods We assessed lymph node invasion (LNI) at final pathology and lymph node (LN) progression during the follow-up for 1983 patients with RCC, treated with either partial or radical nephrectomy. LN progression was defined as the onset of a new clinically detected lymphadenopathy (>10 mm) in the retroperitoneal lymphatic area. Logistic regression analyses were used to assess the effect of each potential clinical predictor (age, body mass index, tumour side, symptoms, performance status, clinical tumour size, clinical tumour-node-metastasis stage, and albumin, calcium, creatinine, haemoglobin and platelet levels) on the outcome of interest. The most parsimonious multivariable predictive model was developed, and discrimination, calibration and net benefit were calculated. Results The prevalence of LNI was 6.1% (120/1983 patients) and during the follow-up period, 82 patients (4.1%) experienced LN progression. On multivariable analyses, the most informative independent predictors were tumour stage (cT3-4 vs cT1-2, odds ratio [OR] 1.52, P = 0.05), clinical nodal status [cN1 vs cN0, OR 7.09, P <0.001], metastases at diagnosis (OR 3.04, P <0.001) and clinical tumour size (OR 1.14, P <0.001). The accuracy of the multivariable model was found to be 86.9%, with excellent calibration and net benefit at decision-curve analyses. Conclusions By relying on a unique approach, combining the risk of harbouring LNI and/or LN progression during the follow-up period, we have provided the first clinical presurgery model predicting the need for LND.

KW - lymph node dissection

KW - lymph node invasion

KW - lymph node progression

KW - lymphadenectomy

KW - nomogram

KW - RCC

KW - renal cell carcinoma

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