• Je něco špatně v tomto záznamu ?

Contemporary Rates and Predictors of Open Conversion During Minimally Invasive Radical Prostatectomy for Nonmetastatic Prostate Cancer

S. Luzzago, G. Rosiello, A. Pecoraro, M. Deuker, F. Stolzenbach, FA. Mistretta, Z. Tian, G. Musi, E. Montanari, SF. Shariat, F. Saad, A. Briganti, O. de Cobelli, PI. Karakiewicz

. 2020 ; 34 (5) : 600-607. [pub] 20200414

Jazyk angličtina Země Spojené státy americké

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/bmc21020584

Background: To test contemporary rates and predictors of open conversion at minimally invasive (laparoscopic or robotic) radical prostatectomy (MIRP). Materials and Methods: Within the National Inpatient Sample database (2008-2015), we identified all MIRP patients and patients who underwent open conversion at MIRP. First, estimated annual percentage changes (EAPCs) tested temporal trends of open conversion. Second, multivariable logistic regression models predicted open conversion at MIRP. All models were weighted and adjusted for clustering, as well as all available patient and hospital characteristics. Results: Of 57,078 MIRP patients, 368 (0.6%) underwent open conversion. The rates of open conversion decreased over time (from 1.80% to 0.38%; EAPC: -26.0%; p = 0.003). In multivariable logistic regression models predicting open conversion, patient obesity (odds ratio [OR]: 2.10; p < 0.001), frailty (OR: 1.45; p = 0.005), and Charlson comorbidity index (CCI) ≥2 (OR: 1.57; p = 0.03) achieved independent predictor status. Moreover, compared with high-volume hospitals, medium-volume (OR: 2.03; p < 0.001) and low-volume hospitals (OR: 3.86; p < 0.001) were associated with higher rates of open conversion. Last but not least, when the interaction between the number of patient risk factors (obesity and/or frailty and/or CCI ≥2) and hospital volume was tested, a dose-response effect was observed. Specifically, the rates of open conversion ranged from 0.3% (patients with zero risk factors treated at high-volume hospitals) to 2.2% (patients with two to three risk factors treated at low-volume hospitals). Conclusion: Overall contemporary (2008-2015) rate of open conversion at MIRP was 0.6% and it was strongly associated with patient obesity, frailty, CCI ≥2, and hospital surgical volume. In consequence, these parameters should be taken into account during preoperative patients counseling, as well as in clinical and administrative decision making.

Citace poskytuje Crossref.org

000      
00000naa a2200000 a 4500
001      
bmc21020584
003      
CZ-PrNML
005      
20210830102227.0
007      
ta
008      
210728s2020 xxu f 000 0|eng||
009      
AR
024    7_
$a 10.1089/end.2020.0074 $2 doi
035    __
$a (PubMed)32178532
040    __
$a ABA008 $b cze $d ABA008 $e AACR2
041    0_
$a eng
044    __
$a xxu
100    1_
$a Luzzago, Stefano $u Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, Quebec, Canada $u Department of Urology, European Institute of Oncology, IRCCS, Milan, Italy
245    10
$a Contemporary Rates and Predictors of Open Conversion During Minimally Invasive Radical Prostatectomy for Nonmetastatic Prostate Cancer / $c S. Luzzago, G. Rosiello, A. Pecoraro, M. Deuker, F. Stolzenbach, FA. Mistretta, Z. Tian, G. Musi, E. Montanari, SF. Shariat, F. Saad, A. Briganti, O. de Cobelli, PI. Karakiewicz
520    9_
$a Background: To test contemporary rates and predictors of open conversion at minimally invasive (laparoscopic or robotic) radical prostatectomy (MIRP). Materials and Methods: Within the National Inpatient Sample database (2008-2015), we identified all MIRP patients and patients who underwent open conversion at MIRP. First, estimated annual percentage changes (EAPCs) tested temporal trends of open conversion. Second, multivariable logistic regression models predicted open conversion at MIRP. All models were weighted and adjusted for clustering, as well as all available patient and hospital characteristics. Results: Of 57,078 MIRP patients, 368 (0.6%) underwent open conversion. The rates of open conversion decreased over time (from 1.80% to 0.38%; EAPC: -26.0%; p = 0.003). In multivariable logistic regression models predicting open conversion, patient obesity (odds ratio [OR]: 2.10; p < 0.001), frailty (OR: 1.45; p = 0.005), and Charlson comorbidity index (CCI) ≥2 (OR: 1.57; p = 0.03) achieved independent predictor status. Moreover, compared with high-volume hospitals, medium-volume (OR: 2.03; p < 0.001) and low-volume hospitals (OR: 3.86; p < 0.001) were associated with higher rates of open conversion. Last but not least, when the interaction between the number of patient risk factors (obesity and/or frailty and/or CCI ≥2) and hospital volume was tested, a dose-response effect was observed. Specifically, the rates of open conversion ranged from 0.3% (patients with zero risk factors treated at high-volume hospitals) to 2.2% (patients with two to three risk factors treated at low-volume hospitals). Conclusion: Overall contemporary (2008-2015) rate of open conversion at MIRP was 0.6% and it was strongly associated with patient obesity, frailty, CCI ≥2, and hospital surgical volume. In consequence, these parameters should be taken into account during preoperative patients counseling, as well as in clinical and administrative decision making.
650    _2
$a lidé $7 D006801
650    12
$a laparoskopie $7 D010535
650    _2
$a mužské pohlaví $7 D008297
650    _2
$a prostatektomie $7 D011468
650    12
$a nádory prostaty $x chirurgie $7 D011471
650    _2
$a rizikové faktory $7 D012307
650    12
$a robotika $7 D012371
655    _2
$a časopisecké články $7 D016428
700    1_
$a Rosiello, Giuseppe $u Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, Quebec, Canada $u Division of Experimental Oncology, Department of Urology, URI, Urological Research Institute, IRCCS San Raffaele Scientific Institute, Milan, Italy
700    1_
$a Pecoraro, Angela $u Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, Quebec, Canada $u Department of Urology, University of Turin, San Luigi Gonzaga Hospital, Turin, Italy
700    1_
$a Deuker, Marina $u Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, Quebec, Canada $u Department of Urology, University Hospital Frankfurt, Frankfurt am Main, Germany
700    1_
$a Stolzenbach, Franziska $u Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, Quebec, Canada $u Martini Klinik, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
700    1_
$a Mistretta, Francesco Alessandro $u Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, Quebec, Canada $u Department of Urology, European Institute of Oncology, IRCCS, Milan, Italy
700    1_
$a Tian, Zhe $u Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, Quebec, Canada
700    1_
$a Musi, Gennaro $u Department of Urology, European Institute of Oncology, IRCCS, Milan, Italy
700    1_
$a Montanari, Emanuele $u Department of Urology, IRCCS Fondazione Ca' Granda-Ospedale Maggiore Policlinico, University of Milan, Milan, Italy
700    1_
$a Shariat, Shahrokh F $u Department of Urology, Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria $u Departments of Urology, Weill Cornell Medical College, New York, New York $u Department of Urology, University of Texas Southwestern, Dallas, Texas $u Department of Urology, Second Faculty of Medicine, Charles University, Prag, Czech Republic $u Institute for Urology and Reproductive Health, I.M. Sechenov First Moscow State Medical University, Moscow, Russia
700    1_
$a Saad, Fred $u Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, Quebec, Canada
700    1_
$a Briganti, Alberto $u Division of Experimental Oncology, Department of Urology, URI, Urological Research Institute, IRCCS San Raffaele Scientific Institute, Milan, Italy
700    1_
$a de Cobelli, Ottavio $u Department of Urology, European Institute of Oncology, IRCCS, Milan, Italy $u Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
700    1_
$a Karakiewicz, Pierre I $u Cancer Prognostics and Health Outcomes Unit, Division of Urology, University of Montreal Health Center, Montreal, Quebec, Canada
773    0_
$w MED00002655 $t Journal of endourology $x 1557-900X $g Roč. 34, č. 5 (2020), s. 600-607
856    41
$u https://pubmed.ncbi.nlm.nih.gov/32178532 $y Pubmed
910    __
$a ABA008 $b sig $c sign $y p $z 0
990    __
$a 20210728 $b ABA008
991    __
$a 20210830102227 $b ABA008
999    __
$a ok $b bmc $g 1691208 $s 1141030
BAS    __
$a 3
BAS    __
$a PreBMC
BMC    __
$a 2020 $b 34 $c 5 $d 600-607 $e 20200414 $i 1557-900X $m Journal of endourology $n J Endourol $x MED00002655
LZP    __
$a Pubmed-20210728

Najít záznam

Citační ukazatele

Možnosti archivace