From Epi to Decisions: Use of Navigation Guide Systematic Review Methodology to Summarize the Evidence for Decision-Making

Friday, May 13, 2016: 5:30 PM-7:00 PM
Hall A (Baltimore Convention Center)
J. Lam1, P. Sutton1, A. Halladay2, A. Kalkbrenner3, G. C. Windham4, L. Davidson5, C. Lawler6, C. J. Newschaffer7, N. Daniels1, S. Sen8 and T. Woodruff1, (1)Program on Reproductive Health and the Environment, University of California, San Francisco, San Francisco, CA, (2)Autism Science Foundation, New York, NY, (3)University of Wisconsin-Milwaukee, Milwaukee, WI, (4)California Department of Public Health, Richmond, CA, (5)University of California at San Francisco, San Francisco, CA, (6)National Institute of Environmental Health Sciences, RTP, NC, (7)A.J. Drexel Autism Institute, Philadelphia, PA, (8)University of California, San Francisco, San Francisco, CA
Background: Evaluating the toxicological and epidemiological literature and determining the quality and strength of evidence are critical for informing health and policy recommendations, including risk of air pollution to ASD. The Navigation Guide was developed through a collaboration of 22 clinicians and scientists to improve methods of research synthesis in environmental health. This systematic and transparent approach is modeled after best practices in evidence-based medicine but accounts for the differences in the evidence and decision context of environmental health.

Objectives: To support proof-of-concept of the method, we applied the Navigation Guide methodology to answer the question: Does developmental exposure to air pollution affect diagnosis of Autism Spectrum Disorder (ASD)? Our intent was to identify and evaluate the relevant body of evidence from human studies and come to a final bottom-line conclusion regarding the quality and strength of evidence to support our study question.

Methods: We gathered a panel of experts with expertise relevant to the study question, developed a protocol, conducted a systematic search of the epidemiology literature, and identified relevant studies using pre-specified criteria. Summary effect estimates from studies were synthesized both qualitatively and quantitatively. We adapted empirically-based clinical medicine quality and risk of bias tools to assess individual studies and to rate the quality and strength of the entire body of evidence for toxicity.

Results: We identified 23 relevant human studies. The human body of evidence was rated as “moderate” quality. Through this case study, we identified several challenges hindering the ease of integrating evidence from different sources of information. In particular, evaluating exposure assessment of air pollution was done using various methods and sources of data (for instance, monitoring, modeling, biomarkers, or a combination of several of these) and reliability of these methods may vary by chemical contaminant. As such, current tools available for evaluating the internal validity of individual studies (i.e., risk of bias) are insufficient for addressing these nuances. Therefore, as part of this case study we modified our current risk of bias tool in a novel attempt to address exposure assessment of air pollution. Furthermore, additional study design and reporting challenges were identified and addressed as potential hindrances to the integration of evidence from different epidemiology studies.

Conclusions: We concluded that there was moderate evidence from the human epidemiology evidence to support an association between developmental exposure to air pollution and diagnosis of ASD. This case study demonstrated that the Navigation Guide can be used to apply the rigor of systematic review methodology to reach actionable conclusions in environmental health decision-making. As part of this case study we also developed a novel risk of bias tool for evaluating the air pollution exposure measurement techniques as well as identified further research limitations potentially hindering the incorporation of epidemiology literature to decision making to protect the public.

See more of: Epidemiology
See more of: Epidemiology