A meta-analysis of robot assisted laparoscopic radical prostatectomy versus laparoscopic radical prostatectomy
Objective: To evaluate the efficacy and safety of robot-assisted laparoscopic radical prostatectomy (RALP) and laparoscopic radical prostatectomy (LRP) for the treatment of localized prostate cancer. Methods: Meta-analysis was applied using Review Manager V5.3 software and the retrieved clinical trials comparing RALP with LRP for the treatment of localized prostate cancer published from 2000 to 2018 in PubMed, Ovid, ScienceDirect, and EMBASE datasets were analyzed. Results: This meta-analysis included 16 articles, totaling 7952 patients, with 5170 RALP patients and 2782 LRP patients. Meta-analysis showed that RALP postoperative complications were fewer (P=0.0007), and the postoperative urinary continence rate was better at 1 year after surgery (P<0.00001). There was no statistical significance between RALP and LRP with regards to the positive incidence of surgical margin (P = 0.18). Conclusion: As an emerging technology, RALP is superior to LRP for localized prostate cancer treatment in terms of postoperative complications, and postoperative urinary continence rate.
- Standort
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                Deutsche Nationalbibliothek Frankfurt am Main
 
- Umfang
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                Online-Ressource
 
- Sprache
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                Englisch
 
- Erschienen in
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                A meta-analysis of robot assisted laparoscopic radical prostatectomy versus laparoscopic radical prostatectomy ; volume:14 ; number:1 ; year:2019 ; pages:485-490 ; extent:6
Open medicine ; 14, Heft 1 (2019), 485-490 (gesamt 6)
 
- Urheber
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                Wang, Tao
Wang, Qunsuo
Wang, Songtao
 
- DOI
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                        10.1515/med-2019-0052
 
- URN
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                        urn:nbn:de:101:1-2022101114093543792603
 
- Rechteinformation
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                        Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
 
- Letzte Aktualisierung
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                        15.08.2025, 07:31 MESZ
 
Datenpartner
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Beteiligte
- Wang, Tao
 - Wang, Qunsuo
 - Wang, Songtao