Systematic comparison of Mendelian randomisation studies and randomised controlled trials using electronic databases

• Published in: BMJ open Vol. 13; no. 9; p. e072087
• Main Authors: Sobczyk, Maria K, Zheng, Jie, Davey Smith, George, Gaunt, Tom R
• Format: Journal Article
• Language: English
• Published: England British Medical Journal Publishing Group 26.09.2023; BMJ Publishing Group LTD; BMJ Publishing Group
• Series: Original research
• Subjects: Cardiovascular disease; Cholesterol; Clinical trials; Confounding (Statistics); Databases, Factual; EPIDEMIOLOGIC STUDIES; Epidemiology; Humans; Intervention; Mendelian Randomization Analysis - methods; Randomized Controlled Trials as Topic; Semantics; Statins; Subject heading schemes; Clinical trials; EPIDEMIOLOGIC STUDIES; EPIDEMIOLOGY
• ISSN: 2044-6055; 2044-6055
• DOI: 10.1136/bmjopen-2023-072087

ObjectiveTo scope the potential for (semi)-automated triangulation of Mendelian randomisation (MR) and randomised controlled trials (RCTs) evidence since the two methods have distinct assumptions that make comparisons between their results invaluable.MethodsWe mined ClinicalTrials.Gov, PubMed and EpigraphDB databases and carried out a series of 26 manual literature comparisons among 54 MR and 77 RCT publications.ResultsWe found that only 13% of completed RCTs identified in ClinicalTrials.Gov submitted their results to the database. Similarly low coverage was revealed for Semantic Medline (SemMedDB) semantic triples derived from MR and RCT publications –36% and 12%, respectively. Among intervention types that can be mimicked by MR, only trials of pharmaceutical interventions could be automatically matched to MR results due to insufficient annotation with Medical Subject Headings ontology. A manual survey of the literature highlighted the potential for triangulation across a number of exposure/outcome pairs if these challenges can be addressed.ConclusionsWe conclude that careful triangulation of MR with RCT evidence should involve consideration of similarity of phenotypes across study designs, intervention intensity and duration, study population demography and health status, comparator group, intervention goal and quality of evidence.