Friday, May 9, 2025
5/9/2025
Meta-analysis of Adverse Drug Effects in Clinical Trials - Project Summary/Abstract Information on drug safety is critical to health care and policy decisions, as treatment recommendations hinge on accurate knowledge of both efficacy and harms. However, assessments of drug safety from individual clinical trials are often underpowered due to insufficient sample sizes and have limited generalizability due to restrictive inclusion/exclusion criteria. Meta-analysis of clinical trials offers a unique opportunity to assess adverse event risks in a large sample size for a broad population, but requires careful consideration of how to handle safety outcomes. Critically, methods that are appropriate for assessing treatment benefits are inappropriate for assessing harms. A key distinction between safety and efficacy data stems from the multifaceted nature of adverse events. There are many types of adverse events, each correlated with different potential risk factors. The severity of these adverse events can vary widely, spanning from mild to fatal. Moreover, many adverse drug effects are infrequent and typically suffer from incomplete reporting. In particular, incomplete reporting of adverse events impacts the ability of systematic reviews to synthesize toxicity data, which can promote a false impression of safety or misinform clinical and regulatory decisions. To address these challenges, we propose to develop novel meta-analytic methods for combining safety data. Specifically, our objectives are to develop meta-analysis approaches that can handle multivariate outcome data, account for the severity of adverse events, and identify potential interactions among risk factors through the following specific aims: Specific Aim 1: To develop meta-analysis methods for multivariate outcomes. Specific Aim 2: To develop methods for meta-analysis with ordinal event grading. Specific Aim 3: To develop a method to identify high-risk subgroups. All methods developed will allow for incomplete reporting and be implemented as easy-to-use software. We will apply the proposed methods to understand the drug toxicity profiles and elucidate risk factors of adverse events resulting from cancer immunotherapy and BTK inhibitors. These findings can be used for risk stratification of patients and to inform potential risk-reduction or monitoring strategies. More broadly, the products of this proposal will promote scientific rigor in summary data integration, allowing appropriate inference on the safety of medical interventions and ultimately enhancing patient care. Our proposed research will establish a new modeling framework that will overcome the limitations of current meta- analysis approaches to synthesize data and information on drug safety. This work directly addresses priorities in the strategic plan of the National Library of Medicine to accelerate discovery and advance health through data-driven research. The new approaches, together with publicly available software, will provide a useful tool for the wider scientific community to conduct more rigorous meta-analysis of safety data.
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