Frontiers in oncology · 2025
Different surgical methods of hysterectomy for the management of endometrial cancer: a systematic review and network meta-analysis.
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Yuan Yuquan, Tan Qin, Chen Yingfan, Zhu Keyang, Pan Bin, Liu Bao, Ren Chunyan, Li Ganghui, Chen Cheng, Zhao Chengzhi
Аннотация
BACKGROUND: Emerging surgical methods are utilized to treat endometrial cancer. The study aimed to assess the efficacy and safety of four common surgical methods of hysterectomy.
METHODS: We systematically searched the PubMed, Cochrane Library databases, Medline, EMBASE and Web of Science from their inception until April 30, 2024. We used hazard ratios (HR) for overall survival (OS) and disease-free (DFS), odds ratios (OR) for categorical outcomes, and mean differences (MD) for continuous outcomes with 95% confidence intervals. These were pooled in Bayesian network meta-analysis models. The surface under the cumulative ranking curve (SUCRA) was used to illuminate the probability that each method would be the best for each outcome.
RESULTS: Thirty studies comprising 13446 patients were included. Robotic hysterectomy (RH) retrieved fewer pelvic lymph nodes than open hysterectomy (OH). OH showed a significantly higher postoperative complication rate than laparoscopic hysterectomy (LH) and RH. LH had a higher intraoperative complication rate than OH. According to SUCRA values, OH ranked the highest in the number of retrieved pelvic lymph nodes (0.89), intraoperative complications (0.73), and operative time (0.97). LH ranked the highest in DFS (0.81) and overall survival (OS) (0.87). RH ranked the highest in the postoperative complications (0.95). Laparoscopic-assisted vaginal hysterectomy (LAVH) ranked the highest in number of retrieved para-aortic lymph nodes (0.72).
CONCLUSIONS: There are no significant differences among the four surgical methods in DFS or OS. The use of uterine manipulators does not affect prognosis. OH is the best method for shortening operative time, dissecting the pelvic lymph nodes and controlling intraoperative complications. LH and LAVH have an advantage in para-aortic lymph node dissection. Besides, LH has the best advantage in DFS and OS. RH has advantages in controlling surgical complications.
SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024529974.
METHODS: We systematically searched the PubMed, Cochrane Library databases, Medline, EMBASE and Web of Science from their inception until April 30, 2024. We used hazard ratios (HR) for overall survival (OS) and disease-free (DFS), odds ratios (OR) for categorical outcomes, and mean differences (MD) for continuous outcomes with 95% confidence intervals. These were pooled in Bayesian network meta-analysis models. The surface under the cumulative ranking curve (SUCRA) was used to illuminate the probability that each method would be the best for each outcome.
RESULTS: Thirty studies comprising 13446 patients were included. Robotic hysterectomy (RH) retrieved fewer pelvic lymph nodes than open hysterectomy (OH). OH showed a significantly higher postoperative complication rate than laparoscopic hysterectomy (LH) and RH. LH had a higher intraoperative complication rate than OH. According to SUCRA values, OH ranked the highest in the number of retrieved pelvic lymph nodes (0.89), intraoperative complications (0.73), and operative time (0.97). LH ranked the highest in DFS (0.81) and overall survival (OS) (0.87). RH ranked the highest in the postoperative complications (0.95). Laparoscopic-assisted vaginal hysterectomy (LAVH) ranked the highest in number of retrieved para-aortic lymph nodes (0.72).
CONCLUSIONS: There are no significant differences among the four surgical methods in DFS or OS. The use of uterine manipulators does not affect prognosis. OH is the best method for shortening operative time, dissecting the pelvic lymph nodes and controlling intraoperative complications. LH and LAVH have an advantage in para-aortic lymph node dissection. Besides, LH has the best advantage in DFS and OS. RH has advantages in controlling surgical complications.
SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024529974.