Comparison of Adverse Event Risks in Randomized Controlled Trials with Varying Follow-Up Times and Competing Events: Results from an Empirical Study

Abstract

Analyses of adverse events (AEs) are an important aspect of the evaluation of experimental therapies. The SAVVY (Survival analysis for AdVerse events with Varying follow-up times) project aims to improve the analyses of AE data in clinical trials through the use of survival techniques appropriately dealing with varying follow-up times, censoring, and competing events (CE). An empirical study including 17 randomized clinical trials investigates the impact on comparisons of two treatment arms with respect to AE risks. The comparisons of relative risks (RR) of standard probability-based estimators to the gold-standard Aalen-Johansen estimator or hazard-based estimators to an estimated hazard ratio (HR) from Cox regression are done descriptively, with graphical displays, and using a random effects meta-analysis on AE level. The influence of different factors on the size of the bias is investigated in a meta-regression. We find that for both, avoiding bias and categorization of evidence with respect to treatment effect on AE risk into categories, the choice of the estimator is key and more important than features of the underlying data such as percentage of censoring, CEs, amount of follow-up, or value of the gold-standard RR. There is an urgent need to improve the guidelines of reporting AEs.

Keywords:

• Adverse events
• Drug safety
• Incidence density
• Incidence proportion
• Risk-benefit assessment

Supplementary Materials

A markdown file providing exemplary code to compute all the estimators discussed in this article for a given dataset is available on github: https://github.com/numbersman77/AEprobs. The corresponding output is available as html file: https://numbersman77.github.io/AEprobs/SAVVY_AEprobs.html.

Disclosure Statement

KR and TK are employees of F. Hoffmann-La Roche (Basel, Switzerland). VJ and CDB are employees of Novartis Pharma AG (Basel, Switzerland). AA, AB, LE, KK, FL, MT, YZ are employees of Merck KGaA (Darmstadt, Germany), Bayer AG (Wuppertal, Germany), Janssen-Cilag GmbH (Neuss, Germany), Bristol-Myers-Squibb GmbH & Co. KGaA (München, Germany), Pfizer Deutschland (Berlin, Germany), Boehringer Ingelheim Pharma GmbH & Co. KG (Ingelheim, Germany), Eli Lilly and Company (Indianapolis, USA), respectively. TF has received personal fees for consultancies (including data monitoring committees) from Bayer, Boehringer Ingelheim, Janssen, Novartis and Roche, all outside the submitted work. JB has received personal fees for consultancy from Pfizer and Roche, all outside the submitted work. CS has received personal fees for consultancies (including data monitoring committees) from Novartis and Roche, all outside the submitted work. The companies mentioned contributed data to the empirical study. RS has declared no conflict of interest.

Funding

The author(s) reported there is no funding associated with the work featured in this article.