The application of two random-effect models for dose-response meta-analysis_Chinese Journal of Evidence-Based Medicine

Authors：

ZHANG Chao ¹ , GAO Zhengyan ² , HUANG Jingyu ³ , LI Sheng ⁴ , NIU Yuming ¹ , XU Chang ⁵ ,  HAN Fangfang ⁶

1. Center for Evidence-Based Medicine and Clinical Research, Taihe Hospital, Hubei University of Medicine, Shiyan, 442000, Hubei, P.R.China;
2. Department of Urology, The Six People’s Hospital of Yancheng, Yancheng, 224000, Hubei, P.R.China;
3. Department of Thoracic Surgery, Hubei Cancer Clinical Study Center and Hubei Key Laboratory of Tumor Biological Behaviors, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, P.R.China;
4. Center for Evidence-Based and Translation Medicine, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, 430071, P.R.China;
5. Chinese Evidence-Based Medicine Center, West China Hospital, Sichuan University, Chengdu, 610041, P. R. China;
6. Department of Ophthalmology, Yuyao No. 2 People's Hospital, Yuyao, 315470, Zhejiang, P.R.China;

Corresponding author：

HAN Fangfang, Email: hanff88@126.com

Keywords：

Dose-response meta-analysis; Two-stage approach; Random-effect model; Stata software

DOI：

10.7507/1672-2531.201703042

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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.

Citation： ZHANG Chao, GAO Zhengyan, HUANG Jingyu, LI Sheng, NIU Yuming, XU Chang, HAN Fangfang. The application of two random-effect models for dose-response meta-analysis. Chinese Journal of Evidence-Based Medicine, 2017, 17(5): 616-620. doi: 10.7507/1672-2531.201703042 Copy

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1. 徐畅, 张永刚, 韩芳芳, 等. 剂量-反应关系 Meta 分析的方法学简介. 中国循证医学杂志, 2015, 15(10): 1236-1239.
2. 徐畅, Suhail A. R. Doi, 张超, 等. 剂量-反应 Meta 分析报告指南(中文版). 中国循证医学杂志, 2016, 16(10): 1221-1226.
3. 黄静宇, 张超, 李胜, 等. 剂量-反应 Meta 分析之限制性立方样条函数的应用. 中国循证医学杂志, 2015, 15(12): 1471-1474.
4. Zhang C, Chen WW, Liu Y, et al. Introduction to methodology of Dose-Response Meta-Analysis with an Application on software. J Evid Based Med. 2017, in press.
5. Liu TZ, Xu C, Rota M, et al. Sleep duration and risk of all-cause mortality: A flexible, non-linear, meta-regression of 40 prospective cohort studies. Sleep Med Rev. 2017, 32: 28-36.
6. Orsini N, Li R, Wolk A, et al. Meta-analysis for linear and nonlinear dose–response relations: examples, an evaluation of approximations, and software. Am J Epidemiol, 2012, 175(1): 66-73.

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