On estimands and the analysis of adverse events in the presence of varying follow-up times within the benefit assessment of therapies

TL;DR

This paper discusses how to properly analyze adverse event data in clinical trials with varying follow-up times, emphasizing the importance of estimands and proposing statistical methods for safety assessment.

Contribution

It introduces the concept of estimands for adverse event analysis, providing tailored statistical methods and practical recommendations for safety evaluation in clinical trials.

Findings

Proposes estimands for adverse event analysis with varying follow-up times

Recommends specific estimators for safety endpoints

Highlights issues in meta-analyses of adverse event data

Abstract

The analysis of adverse events (AEs) is a key component in the assessment of a drug's safety profile. Inappropriate analysis methods may result in misleading conclusions about a therapy's safety and consequently its benefit-risk ratio. The statistical analysis of AEs is complicated by the fact that the follow-up times can vary between the patients included in a clinical trial. This paper takes as its focus the analysis of AE data in the presence of varying follow-up times within the benefit assessment of therapeutic interventions. Instead of approaching this issue directly and solely from an analysis point of view, we first discuss what should be estimated in the context of safety data, leading to the concept of estimands. Although the current discussion on estimands is mainly related to efficacy evaluation, the concept is applicable to safety endpoints as well. Within the framework of estimands, we present statistical methods for analysing AEs with the focus being on the time to the occurrence of the first AE of a specific type. We give recommendations which estimators should be used for the estimands described. Furthermore, we state practical implications of the analysis of AEs in clinical trials and give an overview of examples across different indications. We also provide a review of current practices of health technology assessment (HTA) agencies with respect to the evaluation of safety data. Finally, we describe problems with meta-analyses of AE data and sketch possible solutions.