Meta-analysis using individual patient data from randomised trials to assess the effectiveness of laparoscopic uterosacral nerve ablation in the treatment of chronic pelvic pain: a proposed protocol.

Research output: Contribution to journalArticle

Authors

  • T Xiong
  • N Johnson
  • EM Lichten
  • C Sutton
  • KD Jones
  • FP Chen
  • P Vercellini
  • G Aimi
  • WM Lui

Abstract

BACKGROUND: Currently, there are a number of clinical trials, but no international collaboration for collating research on effectiveness of laparoscopic uterosacral nerve ablation (LUNA) for alleviating chronic pelvic pain. OBJECTIVE: Meta-analysis was used by collecting individual patient data (IPD) from the existing trials, to provide a comprehensive assessment of the effectiveness of LUNA that will be generalisable in various clinical contexts. METHODS: IPD will be sought and collected from all relevant (both already finished and continuing) randomised trials identified through previous systematic reviews. After obtaining raw data and cleaning the database, analysis will be of all patients ever randomised based on the intention-to-treat principle using endpoints measured at 12 months following randomisation. PROPOSAL: We will update searches, contact all authors, obtain data in whatever form it can be provided, build a single database, produce results for individual studies, have them verified by original authors, explore of any heterogeneity and reasons behind it and finally pool all raw data in to a meta-analysis using appropriate statistical methods. The project will test the effectiveness of LUNA for women with chronic pelvic pain. It will also motivate collaborating primary investigators to undertake new primary studies to corroborate or improve upon the conclusions derived from the retrospective analysis.

Details

Original languageEnglish
Pages (from-to)1580, e1-7
JournalBJOG
Volume114
Issue number12
Publication statusPublished - 1 Dec 2007

Keywords

  • meta-analysis, neuroablation, chronic pelvic pain, laparoscopy, individual patient data