Abstract
Background: Human, animal, and cell experimental studies; human biomarker studies; and genetic studies complement epidemiologic findings and can offer insights into biological plausibility and pathways between exposure and disease, but methods for synthesizing such studies are lacking. We, therefore, developed a methodology for identifying mechanisms and carrying out systematic reviews of mechanistic studies that underpin exposure–cancer associations.
Methods: A multidisciplinary team with expertise in informatics, statistics, epidemiology, systematic reviews, cancer biology, and nutrition was assembled. Five 1-day workshops were held to brainstorm ideas; in the intervening periods we carried out searches and applied our methods to a case study to test our ideas.
Results: We have developed a two-stage framework, the first stage of which is designed to identify mechanisms underpinning a specific exposure–disease relationship; the second stage is a targeted systematic review of studies on a specific mechanism. As part of the methodology, we also developed an online tool for text mining for mechanism prioritization (TeMMPo) and a new graph for displaying related but heterogeneous data from epidemiologic studies (the Albatross plot).
Conclusions: We have developed novel tools for identifying mechanisms and carrying out systematic reviews of mechanistic studies of exposure–disease relationships. In doing so, we have outlined how we have overcome the challenges that we faced and provided researchers with practical guides for conducting mechanistic systematic reviews.
Impact: The aforementioned methodology and tools will allow potential mechanisms to be identified and the strength of the evidence underlying a particular mechanism to be assessed.
Methods: A multidisciplinary team with expertise in informatics, statistics, epidemiology, systematic reviews, cancer biology, and nutrition was assembled. Five 1-day workshops were held to brainstorm ideas; in the intervening periods we carried out searches and applied our methods to a case study to test our ideas.
Results: We have developed a two-stage framework, the first stage of which is designed to identify mechanisms underpinning a specific exposure–disease relationship; the second stage is a targeted systematic review of studies on a specific mechanism. As part of the methodology, we also developed an online tool for text mining for mechanism prioritization (TeMMPo) and a new graph for displaying related but heterogeneous data from epidemiologic studies (the Albatross plot).
Conclusions: We have developed novel tools for identifying mechanisms and carrying out systematic reviews of mechanistic studies of exposure–disease relationships. In doing so, we have outlined how we have overcome the challenges that we faced and provided researchers with practical guides for conducting mechanistic systematic reviews.
Impact: The aforementioned methodology and tools will allow potential mechanisms to be identified and the strength of the evidence underlying a particular mechanism to be assessed.
| Original language | English |
|---|---|
| Number of pages | 10 |
| Journal | Cancer Epidemiology, Biomarkers and Prevention |
| Early online date | 4 Oct 2017 |
| DOIs | |
| Publication status | E-pub ahead of print - 4 Oct 2017 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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Dive into the research topics of 'Developing the WCRF International/University of Bristol methodology for identifying and carrying out systematic reviews of mechanisms of exposure-cancer associations'. Together they form a unique fingerprint.Profiles
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Professor Sarah J Lewis
- Epidemiology and Health Data Science - Professor of Molecular Epidemiology
- Bristol Population Health Science Institute
- MRC Integrative Epidemiology Unit
- Cancer
Person: Academic , Member
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Professor Richard M Martin
- Epidemiology and Health Data Science - Associate Pro Vice Chancellor (Research & Innovation) & Professor of Clinical Epidemiology
- Bristol Population Health Science Institute
- MRC Integrative Epidemiology Unit
- Cancer
Person: Academic , Member
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