4.8 Review

A case study applying pathway-oriented thinking to problem formulation for planning a systematic review

Journal

ENVIRONMENT INTERNATIONAL
Volume 140, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.envint.2020.105768

Keywords

Conceptual modelling; Problem formulation; Chemical risk assessment; Systematic review; Aluminium; Breast cancer

Funding

  1. Swiss Federal Food Safety and Veterinary Office [714000548]

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The use of evidence-based methods in chemical risk assessment (CRA) is still in its infancy. Novel approaches exploring how to implement Systematic Review (SR) principles and methods for evaluating human health risks from environmental chemical exposures are needed. This paper reports and comments on a conceptual model that was developed as part of a mapping exercise for planning a SR, using aluminium-containing antiperspirants (Al-AP) and female breast cancer risk as a case study. The work explores how knowledge-assembly tools and pathway-oriented thinking developed in systems toxicology can be applied to support problem formulation (PF) in the context of SR. A conceptual model was developed to map out key research questions, working hypotheses, routes of exposure, toxicity pathways and endpoints, and related health outcomes. The model draws on the analytic framework for screening topics of the U.S. Preventive Services Task Force and builds on the concept of a source-to-outcome continuum, integrating knowledge gained from exposure pathway concepts such as the Aggregate Exposure Pathway and Adverse Outcome Pathways. The model can be used as a central decision and prioritization tool for scoping and framing Population, Exposure, Control, Outcome (PECO) questions in a transparent and iterative manner; as a supporting tool to guide the whole SR process; and to lay down the methodological foundation of a SR on the Al-AP breast cancer topic. Logic modelling can be easily combined with systems or pathway-oriented thinking, and allows for a more structured, objective and transparent approach to PF when applying SR methods to the CRA context.

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