Abstract: Objective To introduce the meta-analysis method for the incidence data using the PROC NLMIXED program in SAS software.Methods A Binomial-Normal model (BNM) or Poisson-Normal model (PNM) based on the generalized linear mixed model (GLMM) was proposed by Stijnen et al., which was extremely convenient to achieve a random-effect meta-analysis of incidence data, especially when the meta-analysis incorporated zero-event studies. A systematic review of the risk of fatal adverse events in cancer patients treated with vascular endothelial growth factor receptor tyrosine kinase inhibitors published by Schutz et al. was used as an example data, and meta-analysis of the incidence data was performed using SAS software and programming code was provided.Results For the zero-event study, the PNM model could be used for meta-analysis without continuity correction. The deletion of the zero-event study could have a greater impact on the PNM model. Compared with the standard normal model, the PNM model or BNM model gave higher effect values, while the P values were smaller, resulting in better sensitivity.Conclusion Based on the generalized linear mixed-effects model, using the PROC NLMIXED in SAS to achieve the meta-analysis of incidence data is the preferred method.

Key words: Binomial-normal model, Generalized linear mixed-effects model, Incidence rate data, Normal-normal model, Poisson-normal model