Data Management And Sharing System of China National Clinical Research Center for Neurological Diseases
Estimate risk difference and number needed to treat in survival analysis
First author：Zhang Zhongheng
Corresponding author：Zhang Zhongheng
essential_information
- Person in charge：Zhang Zhongheng
- Data Sources： OTHERS
- Number of papers：OTHERS20190656
- Published time：2018-04-01
2018-04-01
Published articles
Journal：Ann Transl Med
Publication type: Big-Data Clinical Trial Column
IF(IF): 3.932
PMID: 29955580 Link To Pubmed Full text Download
Background And Purpose
Method
For simplicity, only one measure (RD or NNT) needs to be illustrated, because the other measure is a reverse of the illustrated one (NNT=1/RD). An artificial dataset is composed by using the survsim package. RD and NNT are estimated with Austin method after fitting a Cox-proportional hazard regression model. The confidence intervals can be estimated using bootstrap method. Alternatively, if the standard errors (SEs) of the survival probabilities of the treated and control group are given, confidence intervals can be estimated using algebraic calculations. The pseudo-value model provides another method to estimate RD and NNT. Details of R code and its output are shown and explained in the main text.
Conclusion
The article provides a step-by-step tutorial on the computation of RD and NNT in survival analysis. An artificial dataset containing survival data was employed to illustrate the computation with R. Several methods exist to estimate RD and NNT: the Austin’s method, Altman’s method and pseudo-value procedure. The Altman’s method is used when there is no individual-level data and thus the results may not be comparable to other estimators. The confidence interval can be estimated using bootstrap technique. As compared with RRR, RD or NNT provides more complete information on the risks and benefits of an intervention. In research practice, the rule of thumb is to report both RRR and RD to make the evidence more informative for clinicians and other workers involved in guideline development.