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Developing the WCRF international/University of Bristol methodology for identifying and carrying out systematic reviews of mechanisms of exposure-cancer associations

  • Sarah J Lewis
  • , Mike Gardner
  • , Julian Higgins
  • , Jeff M P Holly
  • , Tom R Gaunt
  • , Claire M Perks
  • , Suzanne D Turner
  • , Sabina Rinaldi
  • , Steve Thomas
  • , Sean Harrison
  • , Rosie J Lennon
  • , Vanessa Tan
  • , Cath Borwick
  • , Pauline Emmett
  • , Mona Jeffreys
  • , Kate Northstone
  • , Giota Mitrou
  • , Martin Wiseman
  • , Rachel Thompson
  • , Richard M Martin

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

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. Cancer Epidemiol Biomarkers Prev; 26(11); 1667-75. ©2017 AACR.

Original languageEnglish
Pages (from-to)1667-1675
Number of pages9
JournalCancer Epidemiology, Biomarkers & Prevention
Volume26
Issue number11
Early online date4 Oct 2017
DOIs
Publication statusPublished - Nov 2017

Bibliographical note

©2017 American Association for Cancer Research.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Biomedical Research/methods
  • Data Mining/methods
  • Evidence-Based Medicine/methods
  • Humans
  • Intersectoral Collaboration
  • Neoplasms/diagnosis
  • Research Design

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