How to Conduct a Dose-response Meta-analysis: The Use of Restricted Cubic Spline Model_Chinese Journal of Evidence-Based Medicine

Authors：

 HUANGJing-yu ¹ , ZHANGChao ² , LISheng ^1,3 , KWONGJoey S. W ⁴ , NIUYu-ming ² ,  XUChang ¹

1. Department of Urology, Zhongnan Hospital, Wuhan University, Wuhan 430071, China;
2. Center for Evidence-based Medicine and Clinical Research, Taihe Hospital, Hubei University of Medicine, Shiyan 442000, China;
3. Center for Evidence-based Medicine, Zhongnan Hospital, Wuhan University, Wuhan 430071, China;
4. Chinese Evidence-based Medicine Center, West China Hospital, Sichuan University, Chengdu 610041, China;

Corresponding author：

XUChang, Email: xuchang1222@126.com

Keywords：

Restricted cubic spine function; Trend approximating; Dose-response meta-analysis; Non-linear relationship

DOI：

10.7507/1672-2531.20150239

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Restricted cubic spline function is an ideal model in trend approximation, which is widely used in doseresponse meta-analysis. The spline function, based on parameter technique, is a smoothly joined piecewise polynomial of each knot, with a cubic polynomial in each sub-interval of the slope which fits well in the non-linear trend by changing the number and (or) the sites of the knots. We have introduced the methodology of linear and non-linear slope model in dose-response meta-analysis in the previous article, and in this one, we will give a more detailed discussion on restricted cubic spline function mainly in the following aspects: model building, parameters pooling and knots selecting.

Citation： HUANGJing-yu, ZHANGChao, LISheng, KWONGJoey S. W, NIUYu-ming, XUChang. How to Conduct a Dose-response Meta-analysis: The Use of Restricted Cubic Spline Model. Chinese Journal of Evidence-Based Medicine, 2015, 15(12): 1471-1474. doi: 10.7507/1672-2531.20150239 Copy

1.	徐畅, 曾宪涛, 张超, 等. 应用R软件dosresmeta程序包和mvmeta 程序包实现剂量-反应关系Meta分析. 中国循证医学杂志, 2015, 15(4):479-483.
2.	Guyatt GH, Oxman AD, Vist GE, et al. GRADE:an emerging consensus on rating quality of evidence and strength of recommendations. BMJ, 2008, 336(7650):924-926.
3.	Durrleman S, Simon R. Flexible regression models with cubic splines. Stat Med, 1989, 8(5):551-561.
4.	Greenland S, Longnecker MP. Methods for trend estimation from summarized dose-response data, with applications to meta-analysis. Am J Epidemiol, 1992, 135(11):1301-1309.
5.	孙振球. 医学统计学. 第3版. 北京:人民卫生出版社, 2002:149-155.
6.	OrsiniN. A procedure to tabulate and plot results after flexible modeling of a quantitative covariate. The Stata Journal, 2011, 11(1): 1-29.
7.	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.
8.	徐畅, 张永刚, 韩芳芳, 等. 剂量反应Meta分析的方法学简介. 中国循证医学杂志, 2015, 15(10):1236-1240.
9.	徐畅, 刘同族, 邝心颖, 等. 剂量-反应Meta分析模型中缺失值的处理及效应指标的转换. 中国循证医学杂志, 2015, 15(8):984-987.

1. 徐畅, 曾宪涛, 张超, 等. 应用R软件dosresmeta程序包和mvmeta 程序包实现剂量-反应关系Meta分析. 中国循证医学杂志, 2015, 15(4):479-483.
2. Guyatt GH, Oxman AD, Vist GE, et al. GRADE:an emerging consensus on rating quality of evidence and strength of recommendations. BMJ, 2008, 336(7650):924-926.
3. Durrleman S, Simon R. Flexible regression models with cubic splines. Stat Med, 1989, 8(5):551-561.
4. Greenland S, Longnecker MP. Methods for trend estimation from summarized dose-response data, with applications to meta-analysis. Am J Epidemiol, 1992, 135(11):1301-1309.
5. 孙振球. 医学统计学. 第3版. 北京:人民卫生出版社, 2002:149-155.
6. OrsiniN. A procedure to tabulate and plot results after flexible modeling of a quantitative covariate. The Stata Journal, 2011, 11(1): 1-29.
7. 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.
8. 徐畅, 张永刚, 韩芳芳, 等. 剂量反应Meta分析的方法学简介. 中国循证医学杂志, 2015, 15(10):1236-1240.
9. 徐畅, 刘同族, 邝心颖, 等. 剂量-反应Meta分析模型中缺失值的处理及效应指标的转换. 中国循证医学杂志, 2015, 15(8):984-987.

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