The use of one-stage meta-analytic method based on individual participant data for binary adverse events under the rule of three: a simulation study

In evidence synthesis practice, dealing with binary rare adverse events (AEs) is a challenging problem. The pooled estimates for rare AEs through traditional inverse variance (IV), Mantel-Haenszel (MH), and Yusuf-Peto (Peto) methods are suboptimal, as the biases tend to be large. We proposed the “one-stage” approach based on multilevel variance component logistic regression (MVCL) to handle this problem