Using New Evidence Synthesis Methods for Decision Making in Reproductive Medicine

Abstract

Pairwise meta-analyses with aggregate data are the current standard method for evidence synthesis in evidence-based medicine. Network meta-analyses and individual participant data (IPD) meta-analyses are relatively new evidence synthesis methods for decision making in health care. Network meta-analyses involve simultaneous comparisons of multiple interventions and IPD meta-analyses provide insights into personalised medicine. These methods have the potential to overcome the drawbacks of conventional evidence synthesis methods and optimise the available evidence and therefore are promising for decision making in reproductive medicine. In this thesis, we applied network meta-analyses to answer a series of clinical questions in reproductive medicine, including the first-line and second-line treatment strategies for polycystic ovary syndrome, clinical managements of unexplained infertility and the use of different contrast media during tubal patency testing to improve fertility outcomes. In addition, we used IPD meta-analysis to identify personalised first-line treatment strategies for polycystic ovary syndrome to improve fertility outcomes. These results can be used to upgrade the current evidence base in reproductive medicine and provide a robust basis for clinical guideline development and directions for future research.