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

Maria K Sobczyk-Barad; Jie Zheng; George Davey Smith; Tom R Gaunt

doi:10.1136/bmjopen-2023-072087

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

Maria K Sobczyk-Barad^*, Jie Zheng, George Davey Smith, Tom R Gaunt

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

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Abstract

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.

Original language	English
Article number	e072087
Number of pages	15
Journal	BMJ Open
Volume	13
Issue number	9
DOIs	https://doi.org/10.1136/bmjopen-2023-072087
Publication status	Published - 26 Sept 2023

Bibliographical note

Funding Information:
We would like to acknowledge UK Medical Research Council [mc_uu_00011/4] which provided funding for our work carried out at the University of Bristol MRC Integrative Epidemiology Unit. Our funder played no role in the design of the study, analysis and interpretation of data and in writing of the manuscript. GDS works within the MRC Integrative Epidemiology Unit at the University of Bristol, which is supported by the Medical Research Council (MC_UU_00011/1).

Funding Information:
JZ, GDS and TG receive funding from Biogen for unrelated research.

Publisher Copyright:
© 2023 BMJ Publishing Group. All rights reserved.

Research Groups and Themes

Bristol Population Health Science Institute

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This is the final published version of the article (version of record). It first appeared online via BMJ at http://dx.doi.org/10.1136/bmjopen-2023-072087 . Please refer to any applicable terms of use of the publisher.
Final published version, 2.11 MBLicence: CC BY

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IEU: MRC Integrative Epidemiology Unit Quinquennial renewal
Gaunt, L. F. (Principal Investigator) & Davey Smith, G. (Principal Investigator)
1/04/18 → 31/03/23
Project: Research

Cite this

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title = "Systematic comparison of Mendelian randomisation studies and randomised controlled trials using electronic databases",

abstract = "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.",

author = "Sobczyk-Barad, \{Maria K\} and Jie Zheng and \{Davey Smith\}, George and Gaunt, \{Tom R\}",

note = "Funding Information: We would like to acknowledge UK Medical Research Council [mc\_uu\_00011/4] which provided funding for our work carried out at the University of Bristol MRC Integrative Epidemiology Unit. Our funder played no role in the design of the study, analysis and interpretation of data and in writing of the manuscript. GDS works within the MRC Integrative Epidemiology Unit at the University of Bristol, which is supported by the Medical Research Council (MC\_UU\_00011/1). Funding Information: JZ, GDS and TG receive funding from Biogen for unrelated research. Publisher Copyright: {\textcopyright} 2023 BMJ Publishing Group. All rights reserved.",

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N1 - Funding Information: We would like to acknowledge UK Medical Research Council [mc_uu_00011/4] which provided funding for our work carried out at the University of Bristol MRC Integrative Epidemiology Unit. Our funder played no role in the design of the study, analysis and interpretation of data and in writing of the manuscript. GDS works within the MRC Integrative Epidemiology Unit at the University of Bristol, which is supported by the Medical Research Council (MC_UU_00011/1). Funding Information: JZ, GDS and TG receive funding from Biogen for unrelated research. Publisher Copyright: © 2023 BMJ Publishing Group. All rights reserved.

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N2 - 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.

AB - 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.

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

Abstract

Bibliographical note

Research Groups and Themes

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Projects

IEU: MRC Integrative Epidemiology Unit Quinquennial renewal

Cite this