Pooling results from epidemiological studies using dose-response meta-analysis

Article type
Authors
Zeraatkar D1, Han M2, Vernooij RR3, Valli C4, Rabassa M4, El Dib R5, Bala MM6, Alonso-Coello P4, Johnston BC7, Guyatt GH1
1Department of Health Research Methods, Evidence, and Impact, McMaster University
2School of Medicine, Chosun University
3Department of Research, Netherlands Comprehensive Cancer Organisation (IKNL)
4Iberoamerican Cochrane Centre Barcelona, Biomedical Research Institute San Pau (IIB Sant Pau)
5Institute of Science and Technology, Universidade Estadual Paulista
6Department of Hygiene and Dietetics, Jagiellonian University Medical College
7Department of Community Health and Epidemiology, Faculty of Medicine, Dalhousie University
Abstract
Background: epidemiological studies typically report on the relationship between levels of exposure to a putative disease-causing agent and risk of disease. Dose-response is considered an important criterion for evaluating the plausibility of causal inferences and is a factor considered in rating the certainty of evidence using the GRADE approach. Dose-response meta-analysis is a statistical method for pooling results from epidemiological studies while taking into account potential dose-response relationships.

Objectives: to present an application of dose-response meta-analysis using our systematic review on the association between red meat consumption and cardiometabolic outcomes as an example.

Methods: we conducted a systematic review of cohort studies reporting on the association between consumption of red meat and adverse cardiometabolic outcomes. We used methods by Greenland & Longnecker to approximate the covariance of relative effects for each study and estimated a corrected trend using generalized least-squares regression. We then pooled study-specific trend estimates using random-effects meta-analysis. We also investigated the possibility of non-linear associations using restricted cubic splines.

Results: we found 55 eligible studies, of which 32 reported sufficient information to be included in dose-response meta-analyses. We found a small positive dose-response association between consumption of red meat and adverse cardiometabolic outcomes with effects associated with decreasing consumption of red meat by three servings/week ranging from risk ratio (RR) 0.90 (95% confidence interval (CI) 0.88 to 0.92) to RR 0.94 (95% CI 0.90 to 0.98) for diabetes and stroke, respectively. We did not find evidence of non-linearity.

Conclusions: dose-response meta-analysis allows estimation of linear and non-linear dose-response relationships across epidemiological studies. Unlike the alternative approach of meta-analyzing relative effects of extreme categories of exposure, dose-response meta-analysis uses all available data without discarding intermediate levels of exposure and considers variations in levels of exposure within and across studies. However, to be eligible for inclusion in dose-response meta-analysis, besides reporting relative effects and their associated variances, studies must additionally report exposure levels and the number of events and participants or person-years across exposure levels.

Patient or healthcare consumer involvement: no patients or consumers were involved in the development or analysis of this study. The study presents an overview of an infrequently used method for meta-analysis, which may improve evidence synthesis, and subsequently improve patient or public health.