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

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 Ep...

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Published inBMJ open Vol. 13; no. 9; p. e072087
Main Authors Sobczyk, Maria K, Zheng, Jie, Davey Smith, George, Gaunt, Tom R
Format Journal Article
LanguageEnglish
Published England British Medical Journal Publishing Group 26.09.2023
BMJ Publishing Group LTD
BMJ Publishing Group
SeriesOriginal 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
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Abstract 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.
AbstractList 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.
Objective To 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.Methods We mined ClinicalTrials.Gov, PubMed and EpigraphDB databases and carried out a series of 26 manual literature comparisons among 54 MR and 77 RCT publications.Results We 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.Conclusions We 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.
To 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. We mined ClinicalTrials.Gov, PubMed and EpigraphDB databases and carried out a series of 26 manual literature comparisons among 54 MR and 77 RCT publications. We 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. We 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.
To 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.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.We mined ClinicalTrials.Gov, PubMed and EpigraphDB databases and carried out a series of 26 manual literature comparisons among 54 MR and 77 RCT publications.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.We 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.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.We 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.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.
Author Gaunt, Tom R
Zheng, Jie
Sobczyk, Maria K
Davey Smith, George
AuthorAffiliation 1 MRC Integrative Epidemiology Unit, Bristol Medical School , University of Bristol , Bristol , UK
3 Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics , Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , People's Republic of China
2 Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases , Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , People's Republic of China
AuthorAffiliation_xml – name: 1 MRC Integrative Epidemiology Unit, Bristol Medical School , University of Bristol , Bristol , UK
– name: 3 Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics , Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , People's Republic of China
– name: 2 Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases , Ruijin Hospital, Shanghai Jiao Tong University School of Medicine , Shanghai , People's Republic of China
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  givenname: Maria K
  orcidid: 0000-0003-0000-4100
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  organization: MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
– sequence: 2
  givenname: Jie
  orcidid: 0000-0002-6623-6839
  surname: Zheng
  fullname: Zheng, Jie
  organization: Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/37751957$$D View this record in MEDLINE/PubMed
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Thu Aug 21 18:36:17 EDT 2025
Mon Jul 21 09:31:18 EDT 2025
Fri Jul 25 21:37:57 EDT 2025
Mon Jul 21 05:52:28 EDT 2025
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Issue 9
Keywords Clinical trials
EPIDEMIOLOGIC STUDIES
EPIDEMIOLOGY
Language English
License This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.
Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY. Published by BMJ.
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SSID ssj0000459552
Score 2.4204233
Snippet ObjectiveTo scope the potential for (semi)-automated triangulation of Mendelian randomisation (MR) and randomised controlled trials (RCTs) evidence since the...
To scope the potential for (semi)-automated triangulation of Mendelian randomisation (MR) and randomised controlled trials (RCTs) evidence since the two...
Objective To scope the potential for (semi)-automated triangulation of Mendelian randomisation (MR) and randomised controlled trials (RCTs) evidence since the...
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StartPage e072087
SubjectTerms 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
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Title Systematic comparison of Mendelian randomisation studies and randomised controlled trials using electronic databases
URI https://bmjopen.bmj.com/content/13/9/e072087.full
https://www.ncbi.nlm.nih.gov/pubmed/37751957
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Volume 13
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