谷歌浏览器插件
订阅小程序
在清言上使用

[A meta-analysis of preventing bone mineral loss in patients with endometriosis treated by gonadotrophin-releasing hormone analogues with add-back therapy].

Zhonghua fu chan ke za zhi(2013)

引用 4|浏览40
暂无评分
摘要
OBJECTIVE:To evaluate the role and efficacy of preventing bone mineral loss in patients with endometriosis treated by gonadotrophin-releasing hormone analogues (GnRH-a) combined with add-back therapy. METHODS:Prospective, randomized controlled studies of the use of GnRHa with add-back therapy in treatment of endometriosis were enrolled in this study from Medline, Embase, Cochrane library, China National Knowledge Internet (CNKI), Chinese Biological Medicine Disk (CBM) and Data Base of Wanfang.After quality assessment and data extraction, meta-analysis were conducted in the change of BMD, reproductive hormone (E2) and visual pain score(VAS) by Stata 11.0 software. RESULTS:A total of 785 patients from 13 randomized controlled trail (RCT) studies enrolled in this study after exclude no following up, poor quality and repeat published studies.377 patients were in group of GnRH-a with add-back treatment and 408 patients were in group of GnRna alone.The findinds were showed in meta-analysis: (1) there was a significant difference in percentage change of bone mineral density (BMD) between two groups, the add-back therapy was more effective in prevention of bone loss which was (SMD = 0.223, 95%CI:0.003 to 0.443, P = 0.047). (2) There was no significant difference in the level of reproductive hormone between two groups (SMD = -0.053, 95% CI:-0.479 to 0.373, P = 0.807). (3) There was also no significant difference in the visual pain score between the two groups (SMD = -0.157, 95% CI: -0.474 to 0.160, P = 0.332). CONCLUSIONS:GnRH-a with add-back therapy have been shown to be more effective in preventing loss of BMD than GnRH-a treatment alone.However, the long term effect of preventing BMD should be studied.
更多
查看译文
关键词
Gonadotropin-releasing hormone,Estrogens,Endometriosis,Bone density,Meta-analysis
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要