Dose-response meta-analysis is being increasingly applied in evidence production and clinical decision. The research method, synthesizing certain dose-specific effects across studies with the same target question by a certain types of weighting schedule to get a mean dose-response effect, is to reflect the dose-response relationship between certain exposure and outcome. Currently, the most popular method for dose-response meta-analysis is based on the classical "two-stage approach", with the advantage that it allows fixed- or random-effect model, according to the amount of heterogeneity in the model. There are two types of random-effect model available for dose-response meta-analysis, that is, the generally model and the coefficient-correlation-adjusted model. In this article, we briefly introduce two models and illustrate how they are applied in Stata software, which is expected to provide theoretical foundation for evidence-based practice.
Dose-response meta-analysis (DRMA) is one of the branches of meta-analysis, which has provided important evidence for clinical research. Since introducing into China, it has gained great attention. In order to improve the reporting quality of DRMA, Dr. Chang Xu et al. developed the reporting guideline for DAMA——G-Dose Checklist. It was published in Chinese Jouranl of Evidence-based Medicine in 2016. This paper interprets the checklists so as to promote the understanding and use of it.