Radiographic size of retroperitoneal lymph nodes predicts pathological nodal involvement for patients with renal cell carcinoma: development of a risk prediction model

Boris Gershman, Naoki Takahashi, Daniel M. Moreira, Robert H. Thompson, Stephen A. Boorjian, Christine M. Lohse, Brian Costello, John C. Cheville, Bradley C. Leibovich

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Objectives: To evaluate the ability of clinical and radiographic features to predict lymph node (pN1) disease among patients with renal cell carcinoma undergoing radical nephrectomy (RN), and to develop a preoperative risk prediction model. Patients and Methods: In all, 220 patients with preoperative computed tomography scans available for review underwent RN with lymph node dissection (LND) from 2000 to 2010. Radiographic features were assessed by one genitourinary radiologist blinded to pN status. Associations of features with pN1 disease were evaluated using logistic regression to develop predictive models. Model performance was assessed using area under the receiver operating characteristic curve (AUC) and decision curve analysis. Results: The median (interquartile range) lymph node yield was 10 (5-18). In all, 55 patients (25%) had pN1 disease at RN. On univariable analysis, the maximum lymph node (LN) short axis diameter [odds ratio (OR) 1.17; P <0.001] predicted pN1 disease with an AUC of 0.84. Although several clinical and radiographic features were associated with pN1 disease, only two were retained in the multivariable model: maximum LN short axis diameter (OR 1.19; P

Original languageEnglish (US)
JournalBJU International
DOIs
StateAccepted/In press - 2016

Fingerprint

Renal Cell Carcinoma
Lymph Nodes
Nephrectomy
Area Under Curve
Odds Ratio
Decision Support Techniques
Lymph Node Excision
ROC Curve
Logistic Models
Tomography

Keywords

  • Lymph node dissection
  • Lymphadenopathy
  • Nephrectomy
  • Node positive
  • Renal cell carcinoma

ASJC Scopus subject areas

  • Urology

Cite this

Radiographic size of retroperitoneal lymph nodes predicts pathological nodal involvement for patients with renal cell carcinoma : development of a risk prediction model. / Gershman, Boris; Takahashi, Naoki; Moreira, Daniel M.; Thompson, Robert H.; Boorjian, Stephen A.; Lohse, Christine M.; Costello, Brian; Cheville, John C.; Leibovich, Bradley C.

In: BJU International, 2016.

Research output: Contribution to journalArticle

Gershman, Boris ; Takahashi, Naoki ; Moreira, Daniel M. ; Thompson, Robert H. ; Boorjian, Stephen A. ; Lohse, Christine M. ; Costello, Brian ; Cheville, John C. ; Leibovich, Bradley C. / Radiographic size of retroperitoneal lymph nodes predicts pathological nodal involvement for patients with renal cell carcinoma : development of a risk prediction model. In: BJU International. 2016.
@article{0f96f4260aac434a8a78fb1679ad619a,
title = "Radiographic size of retroperitoneal lymph nodes predicts pathological nodal involvement for patients with renal cell carcinoma: development of a risk prediction model",
abstract = "Objectives: To evaluate the ability of clinical and radiographic features to predict lymph node (pN1) disease among patients with renal cell carcinoma undergoing radical nephrectomy (RN), and to develop a preoperative risk prediction model. Patients and Methods: In all, 220 patients with preoperative computed tomography scans available for review underwent RN with lymph node dissection (LND) from 2000 to 2010. Radiographic features were assessed by one genitourinary radiologist blinded to pN status. Associations of features with pN1 disease were evaluated using logistic regression to develop predictive models. Model performance was assessed using area under the receiver operating characteristic curve (AUC) and decision curve analysis. Results: The median (interquartile range) lymph node yield was 10 (5-18). In all, 55 patients (25{\%}) had pN1 disease at RN. On univariable analysis, the maximum lymph node (LN) short axis diameter [odds ratio (OR) 1.17; P <0.001] predicted pN1 disease with an AUC of 0.84. Although several clinical and radiographic features were associated with pN1 disease, only two were retained in the multivariable model: maximum LN short axis diameter (OR 1.19; P",
keywords = "Lymph node dissection, Lymphadenopathy, Nephrectomy, Node positive, Renal cell carcinoma",
author = "Boris Gershman and Naoki Takahashi and Moreira, {Daniel M.} and Thompson, {Robert H.} and Boorjian, {Stephen A.} and Lohse, {Christine M.} and Brian Costello and Cheville, {John C.} and Leibovich, {Bradley C.}",
year = "2016",
doi = "10.1111/bju.13424",
language = "English (US)",
journal = "BJU International",
issn = "1464-4096",
publisher = "Wiley-Blackwell",

}

TY - JOUR

T1 - Radiographic size of retroperitoneal lymph nodes predicts pathological nodal involvement for patients with renal cell carcinoma

T2 - development of a risk prediction model

AU - Gershman, Boris

AU - Takahashi, Naoki

AU - Moreira, Daniel M.

AU - Thompson, Robert H.

AU - Boorjian, Stephen A.

AU - Lohse, Christine M.

AU - Costello, Brian

AU - Cheville, John C.

AU - Leibovich, Bradley C.

PY - 2016

Y1 - 2016

N2 - Objectives: To evaluate the ability of clinical and radiographic features to predict lymph node (pN1) disease among patients with renal cell carcinoma undergoing radical nephrectomy (RN), and to develop a preoperative risk prediction model. Patients and Methods: In all, 220 patients with preoperative computed tomography scans available for review underwent RN with lymph node dissection (LND) from 2000 to 2010. Radiographic features were assessed by one genitourinary radiologist blinded to pN status. Associations of features with pN1 disease were evaluated using logistic regression to develop predictive models. Model performance was assessed using area under the receiver operating characteristic curve (AUC) and decision curve analysis. Results: The median (interquartile range) lymph node yield was 10 (5-18). In all, 55 patients (25%) had pN1 disease at RN. On univariable analysis, the maximum lymph node (LN) short axis diameter [odds ratio (OR) 1.17; P <0.001] predicted pN1 disease with an AUC of 0.84. Although several clinical and radiographic features were associated with pN1 disease, only two were retained in the multivariable model: maximum LN short axis diameter (OR 1.19; P

AB - Objectives: To evaluate the ability of clinical and radiographic features to predict lymph node (pN1) disease among patients with renal cell carcinoma undergoing radical nephrectomy (RN), and to develop a preoperative risk prediction model. Patients and Methods: In all, 220 patients with preoperative computed tomography scans available for review underwent RN with lymph node dissection (LND) from 2000 to 2010. Radiographic features were assessed by one genitourinary radiologist blinded to pN status. Associations of features with pN1 disease were evaluated using logistic regression to develop predictive models. Model performance was assessed using area under the receiver operating characteristic curve (AUC) and decision curve analysis. Results: The median (interquartile range) lymph node yield was 10 (5-18). In all, 55 patients (25%) had pN1 disease at RN. On univariable analysis, the maximum lymph node (LN) short axis diameter [odds ratio (OR) 1.17; P <0.001] predicted pN1 disease with an AUC of 0.84. Although several clinical and radiographic features were associated with pN1 disease, only two were retained in the multivariable model: maximum LN short axis diameter (OR 1.19; P

KW - Lymph node dissection

KW - Lymphadenopathy

KW - Nephrectomy

KW - Node positive

KW - Renal cell carcinoma

UR - http://www.scopus.com/inward/record.url?scp=84959387119&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84959387119&partnerID=8YFLogxK

U2 - 10.1111/bju.13424

DO - 10.1111/bju.13424

M3 - Article

C2 - 26800148

AN - SCOPUS:84959387119

JO - BJU International

JF - BJU International

SN - 1464-4096

ER -