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A population based assessment of perioperative mortality after cystectomy for bladder cancer.

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A population based assessment of perioperative mortality after cystectomy for bladder cancer. / Isbarn, Hendrik; Jeldres, Claudio; Zini, Laurent; Perrotte, Paul; Baillargeon-Gagne, Sara; Capitanio, Umberto; Shariat, Shahrokh F; Arjane, Phillipe; Saad, Fred; McCormack, Michael; Valiquette, Luc; Peloquin, Francois; Duclos, Alain; Montorsi, Francesco; Graefen, Markus; Karakiewicz, Pierre I.

in: J UROLOGY, Jahrgang 182, Nr. 1, 1, 2009, S. 70-77.

Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung

Harvard

Isbarn, H, Jeldres, C, Zini, L, Perrotte, P, Baillargeon-Gagne, S, Capitanio, U, Shariat, SF, Arjane, P, Saad, F, McCormack, M, Valiquette, L, Peloquin, F, Duclos, A, Montorsi, F, Graefen, M & Karakiewicz, PI 2009, 'A population based assessment of perioperative mortality after cystectomy for bladder cancer.', J UROLOGY, Jg. 182, Nr. 1, 1, S. 70-77. <http://www.ncbi.nlm.nih.gov/pubmed/19447427?dopt=Citation>

APA

Isbarn, H., Jeldres, C., Zini, L., Perrotte, P., Baillargeon-Gagne, S., Capitanio, U., Shariat, S. F., Arjane, P., Saad, F., McCormack, M., Valiquette, L., Peloquin, F., Duclos, A., Montorsi, F., Graefen, M., & Karakiewicz, P. I. (2009). A population based assessment of perioperative mortality after cystectomy for bladder cancer. J UROLOGY, 182(1), 70-77. [1]. http://www.ncbi.nlm.nih.gov/pubmed/19447427?dopt=Citation

Vancouver

Isbarn H, Jeldres C, Zini L, Perrotte P, Baillargeon-Gagne S, Capitanio U et al. A population based assessment of perioperative mortality after cystectomy for bladder cancer. J UROLOGY. 2009;182(1):70-77. 1.

Bibtex

@article{04fc6354480341548ea1fa052b2c8df9,
title = "A population based assessment of perioperative mortality after cystectomy for bladder cancer.",
abstract = "PURPOSE: Large variability exists in the rates of perioperative mortality after cystectomy. Contemporary estimates range from 0.7% to 5.6%. We tested several predictors of perioperative mortality and devised a model for individual perioperative mortality prediction. MATERIALS AND METHODS: We relied on life tables to quantify 30, 60 and 90-day mortality rates according to age, gender, stage (localized vs regional), grade, type of surgery (partial vs radical cystectomy), year of cystectomy and histological bladder cancer subtype. We fitted univariable and multivariable logistic regression models using 5,510 patients diagnosed with bladder cancer and treated with partial or radical cystectomy within 4 SEER (Surveillance, Epidemiology, and End Results) registries between 1984 and 2004. We then externally validated the model on 5,471 similar patients from 5 other SEER registries. RESULTS: At 30, 60 and 90 days the perioperative mortality rates were 1.1%, 2.4% and 3.9%, respectively. Age, stage and histological subtype represented statistically significant and independent predictors of 90-day mortality. The combined use of these 3 variables and of tumor grade resulted in the most accurate model (70.1%) for prediction of individual probability of 90-day mortality after cystectomy. CONCLUSIONS: The accuracy of our model could potentially be improved with the consideration of additional parameters such as surgical and hospital volume or comorbidity. While better models are being developed and tested we suggest the use of the current model in individual decision making and in informed consent considerations because it provides accurate predictions in 7 of 10 patients.",
author = "Hendrik Isbarn and Claudio Jeldres and Laurent Zini and Paul Perrotte and Sara Baillargeon-Gagne and Umberto Capitanio and Shariat, {Shahrokh F} and Phillipe Arjane and Fred Saad and Michael McCormack and Luc Valiquette and Francois Peloquin and Alain Duclos and Francesco Montorsi and Markus Graefen and Karakiewicz, {Pierre I}",
year = "2009",
language = "Deutsch",
volume = "182",
pages = "70--77",
journal = "J UROLOGY",
issn = "0022-5347",
publisher = "Elsevier Inc.",
number = "1",

}

RIS

TY - JOUR

T1 - A population based assessment of perioperative mortality after cystectomy for bladder cancer.

AU - Isbarn, Hendrik

AU - Jeldres, Claudio

AU - Zini, Laurent

AU - Perrotte, Paul

AU - Baillargeon-Gagne, Sara

AU - Capitanio, Umberto

AU - Shariat, Shahrokh F

AU - Arjane, Phillipe

AU - Saad, Fred

AU - McCormack, Michael

AU - Valiquette, Luc

AU - Peloquin, Francois

AU - Duclos, Alain

AU - Montorsi, Francesco

AU - Graefen, Markus

AU - Karakiewicz, Pierre I

PY - 2009

Y1 - 2009

N2 - PURPOSE: Large variability exists in the rates of perioperative mortality after cystectomy. Contemporary estimates range from 0.7% to 5.6%. We tested several predictors of perioperative mortality and devised a model for individual perioperative mortality prediction. MATERIALS AND METHODS: We relied on life tables to quantify 30, 60 and 90-day mortality rates according to age, gender, stage (localized vs regional), grade, type of surgery (partial vs radical cystectomy), year of cystectomy and histological bladder cancer subtype. We fitted univariable and multivariable logistic regression models using 5,510 patients diagnosed with bladder cancer and treated with partial or radical cystectomy within 4 SEER (Surveillance, Epidemiology, and End Results) registries between 1984 and 2004. We then externally validated the model on 5,471 similar patients from 5 other SEER registries. RESULTS: At 30, 60 and 90 days the perioperative mortality rates were 1.1%, 2.4% and 3.9%, respectively. Age, stage and histological subtype represented statistically significant and independent predictors of 90-day mortality. The combined use of these 3 variables and of tumor grade resulted in the most accurate model (70.1%) for prediction of individual probability of 90-day mortality after cystectomy. CONCLUSIONS: The accuracy of our model could potentially be improved with the consideration of additional parameters such as surgical and hospital volume or comorbidity. While better models are being developed and tested we suggest the use of the current model in individual decision making and in informed consent considerations because it provides accurate predictions in 7 of 10 patients.

AB - PURPOSE: Large variability exists in the rates of perioperative mortality after cystectomy. Contemporary estimates range from 0.7% to 5.6%. We tested several predictors of perioperative mortality and devised a model for individual perioperative mortality prediction. MATERIALS AND METHODS: We relied on life tables to quantify 30, 60 and 90-day mortality rates according to age, gender, stage (localized vs regional), grade, type of surgery (partial vs radical cystectomy), year of cystectomy and histological bladder cancer subtype. We fitted univariable and multivariable logistic regression models using 5,510 patients diagnosed with bladder cancer and treated with partial or radical cystectomy within 4 SEER (Surveillance, Epidemiology, and End Results) registries between 1984 and 2004. We then externally validated the model on 5,471 similar patients from 5 other SEER registries. RESULTS: At 30, 60 and 90 days the perioperative mortality rates were 1.1%, 2.4% and 3.9%, respectively. Age, stage and histological subtype represented statistically significant and independent predictors of 90-day mortality. The combined use of these 3 variables and of tumor grade resulted in the most accurate model (70.1%) for prediction of individual probability of 90-day mortality after cystectomy. CONCLUSIONS: The accuracy of our model could potentially be improved with the consideration of additional parameters such as surgical and hospital volume or comorbidity. While better models are being developed and tested we suggest the use of the current model in individual decision making and in informed consent considerations because it provides accurate predictions in 7 of 10 patients.

M3 - SCORING: Zeitschriftenaufsatz

VL - 182

SP - 70

EP - 77

JO - J UROLOGY

JF - J UROLOGY

SN - 0022-5347

IS - 1

M1 - 1

ER -