Enrichment of the knowledge and methodology to evaluate the transitivity and consistency assumptions in complex networks of interventions

• Applicant: Privatdozentin Dr. Loukia Spineli
• Subject Area: Epidemiology and Medical Biometry/Statistics
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 462260733

Systematic reviews with network meta-analysis (NMA) play a crucial role in producing the best evidence for several competing interventions. The explosive rate of such published reviews attests to the popularity of this evidence tool in the broad medical community. In particular, the pressure of the COVID-19 pandemic globally to promote timely evidence-based recommendations for numerous prescribed interventions (with many of them being off-label) renders NMA more necessary than ever. Nevertheless, the quality of the conclusions delivered to the end-users strongly depends on whether the underlying assumptions that define NMA are valid. These assumptions refer to the similarity of the synthesised evidence, based on epidemiological and statistical grounds, and they are known as transitivity and consistency. There is a vast literature on the concepts and methods that relate to transitivity and consistency assumptions. However, the findings of several empirical studies on the reporting and evaluation quality of these assumptions have been underwhelming. Furthermore, most of these empirical studies have focused mainly on networks of three interventions. Therefore, their findings cannot be generalised to reviews that include complex networks of interventions. Another major limitation these studies is their undue reliance on the p-value to infer the similarity of the synthesised evidence. Thorough improvement in the reporting and evaluation of the transitivity and consistency assumptions requires the development of objective and validated methods to engage the authors of systematic reviews in that direction. The present proposal aspires to foster the systematic evaluation of the underlying assumptions of NMA while using proper methods, and ultimately, to upgrade the quality of the conclusions delivered to the end-users. The concrete objectives of the research agenda are two-fold: to update the evidence on the reporting quality and evaluation of the transitivity assumption in complex networks, and to promote novel approaches to judge the epidemiological and statistical similarity of the collated evidence objectively without undue reliance on statistical tests.

• DFG Programme: Research Grants