Caveats of Covariate Adjustment in Disproportionality Analysis for Best Practices

Spontaneous reporting systems (SRS) provide valuable data for detecting unidentified adverse events not observed in clinical trials and for conducting safety assessments that accurately reflect real-world clinical practice. With the increasing number of publications using the SRS for disproportionality analysis (DA), there is an increasing demand for a comprehensive understanding of the research limitations associated with the SRS. However, there is a lack of understanding of the caveats associated with adjusting covariates in DA of the SRS. Herein, we summarized the use of covariate adjustment and its caveats in DA. The Council for International Organizations of Medical Sciences VIII suggests considering adjustments such as stratification when they can enhance the sensitivity and/or specificity of statistical analysis. However, several database-specific and statistical caveats have been identified when adjusting for covariates derived from the SRS. Disproportionality analysis may be affected not only by reporting bias at the time of enrollment but also by sparse-data bias due to variations in the number of enrollment reports. Statistical evidence is needed to determine in which cases and to what extent sensitivity and/or specificity are affected. Nevertheless, it is important for researchers to acknowledge that certain limitations discussed in this context may be inherent and cannot be rectified. Based on this understanding, they can then make an informed decision on whether to perform a covariate adjustment.