Development of accurate models for individualized prediction of survival after cytoreductive nephrectomy for metastatic renal cell carcinoma
Standard
Development of accurate models for individualized prediction of survival after cytoreductive nephrectomy for metastatic renal cell carcinoma. / Margulis, Vitaly; Shariat, Shahrokh F; Rapoport, Yury; Rink, Michael; Sjoberg, Daniel D; Tannir, Nizar M; Abel, E Jason; Culp, Stephen H; Tamboli, Pheroze; Wood, Christopher G.
In: EUR UROL, Vol. 63, No. 5, 01.05.2013, p. 947-52.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
Harvard
APA
Vancouver
Bibtex
}
RIS
TY - JOUR
T1 - Development of accurate models for individualized prediction of survival after cytoreductive nephrectomy for metastatic renal cell carcinoma
AU - Margulis, Vitaly
AU - Shariat, Shahrokh F
AU - Rapoport, Yury
AU - Rink, Michael
AU - Sjoberg, Daniel D
AU - Tannir, Nizar M
AU - Abel, E Jason
AU - Culp, Stephen H
AU - Tamboli, Pheroze
AU - Wood, Christopher G
N1 - Copyright © 2012. Published by Elsevier B.V.
PY - 2013/5/1
Y1 - 2013/5/1
N2 - BACKGROUND: There is limited evidence to guide patient selection for cytoreductive nephrectomy (CN) following the diagnosis of metastatic renal cell carcinoma (mRCC).OBJECTIVE: Given the significant variability in oncologic outcomes following surgery, we sought to develop clinically relevant, individualized, multivariable models for the prediction of cancer-specific survival at 6 and 12 mo after CN. The development of this nomogram will better help clinicians select patients for cytoreductive surgery.DESIGN, SETTING, AND PARTICIPANTS: We identified 601 consecutive patients who underwent CN for kidney cancer at a single tertiary cancer center.INTERVENTION: CN for mRCC.OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The development cohort was used to select predictive variables from a large group of candidate predictors. The discrimination, calibration, and decision curves were corrected for overfit using 10-fold crossvalidation that included stepwise variable selection.RESULTS AND LIMITATIONS: With a median follow-up of 65 mo (range: 6-199) for the entire cohort, 110 and 215 patients died from kidney cancer at 6 and 12 mo after surgery, respectively. For the preoperative model, serum albumin and serum lactate dehydrogenase were included. Final pathologic primary tumor stage, nodal stage, and receipt of blood transfusion were added to the previously mentioned parameters for the postoperative model. Preoperative and postoperative nomograms demonstrated good discrimination of 0.76 and 0.74, respectively, when applied to the validation data set. Both models demonstrated excellent calibration and a good net benefit over large ranges of threshold probabilities. The retrospective study design is the major limitation of this study.CONCLUSIONS: We have developed models for accurate prediction of cancer-specific survival after CN, using either preoperative or postoperative variables. While these tools need validation in independent cohorts, our results suggest that the models are informative and can be used to aid in clinical decision making.
AB - BACKGROUND: There is limited evidence to guide patient selection for cytoreductive nephrectomy (CN) following the diagnosis of metastatic renal cell carcinoma (mRCC).OBJECTIVE: Given the significant variability in oncologic outcomes following surgery, we sought to develop clinically relevant, individualized, multivariable models for the prediction of cancer-specific survival at 6 and 12 mo after CN. The development of this nomogram will better help clinicians select patients for cytoreductive surgery.DESIGN, SETTING, AND PARTICIPANTS: We identified 601 consecutive patients who underwent CN for kidney cancer at a single tertiary cancer center.INTERVENTION: CN for mRCC.OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The development cohort was used to select predictive variables from a large group of candidate predictors. The discrimination, calibration, and decision curves were corrected for overfit using 10-fold crossvalidation that included stepwise variable selection.RESULTS AND LIMITATIONS: With a median follow-up of 65 mo (range: 6-199) for the entire cohort, 110 and 215 patients died from kidney cancer at 6 and 12 mo after surgery, respectively. For the preoperative model, serum albumin and serum lactate dehydrogenase were included. Final pathologic primary tumor stage, nodal stage, and receipt of blood transfusion were added to the previously mentioned parameters for the postoperative model. Preoperative and postoperative nomograms demonstrated good discrimination of 0.76 and 0.74, respectively, when applied to the validation data set. Both models demonstrated excellent calibration and a good net benefit over large ranges of threshold probabilities. The retrospective study design is the major limitation of this study.CONCLUSIONS: We have developed models for accurate prediction of cancer-specific survival after CN, using either preoperative or postoperative variables. While these tools need validation in independent cohorts, our results suggest that the models are informative and can be used to aid in clinical decision making.
KW - Blood Transfusion
KW - Carcinoma, Renal Cell
KW - Decision Support Techniques
KW - Disease-Free Survival
KW - Female
KW - Humans
KW - Individualized Medicine
KW - Kidney Neoplasms
KW - L-Lactate Dehydrogenase
KW - Logistic Models
KW - Male
KW - Middle Aged
KW - Multivariate Analysis
KW - Neoplasm Staging
KW - Nephrectomy
KW - Odds Ratio
KW - Patient Selection
KW - Retrospective Studies
KW - Risk Assessment
KW - Risk Factors
KW - Serum Albumin
KW - Tertiary Care Centers
KW - Texas
KW - Time Factors
KW - Treatment Outcome
KW - Tumor Markers, Biological
U2 - 10.1016/j.eururo.2012.11.040
DO - 10.1016/j.eururo.2012.11.040
M3 - SCORING: Journal article
C2 - 23273681
VL - 63
SP - 947
EP - 952
JO - EUR UROL
JF - EUR UROL
SN - 0302-2838
IS - 5
ER -
