Objective To introduce the multivariate random effects model (MREM) in the meta-analysis of diagnostic tests with multiple thresholds. Methods This paper expanded and extended the bivariate random effects model (BREM) to develop the MREM, and implemented it in the SAS Proc NLMIXED procedure. Results The MREM could obtain the study specific ROC curve for each study through empirical Bayes estimation, and the summary ROC curve located in between all study specific ROC curves evenly, while the BREM couldn’t obtain the study specific ROC curve. In addition, in the aspect of parameters estimation, the MREM didn’t depend on the choice of the diagnosis threshold and the type of SROC. The MREM could get only one SROC curve and its AUC was between the AUC of the 5 types of SROC from BREM, so it could avoid overestimation or underestimation. Conclusion The MREM can fully exploit the data, obtain stable and reliable results, and have a good application value in meta-analysis of diagnostic tests with multiple thresholds.