Accurate collection of reasons for treatment discontinuation to better define estimands in clinical trials

TL;DR

This paper analyzes how current clinical trial forms inadequately record reasons for treatment discontinuation and proposes systematic improvements to enhance data accuracy for better estimand definition.

Contribution

It introduces a systematic review of discontinuation data and suggests an improved CRF design to accurately capture reasons for treatment discontinuation in clinical trials.

Findings

Current CRFs often record vague reasons for discontinuation.

Different underlying reasons can be misclassified under the same category.

Proposed systematic approach improves accuracy of discontinuation data collection.

Abstract

Background: Reasons for treatment discontinuation are important not only to understand the benefit and risk profile of experimental treatments, but also to help choose appropriate strategies to handle intercurrent events in defining estimands. The current case report form (CRF) commonly in use mixes the underlying reasons for treatment discontinuation and who makes the decision for treatment discontinuation, often resulting in an inaccurate collection of reasons for treatment discontinuation. Methods and results: We systematically reviewed and analyzed treatment discontinuation data from nine phase 2 and phase 3 studies for insulin peglispro. A total of 857 participants with treatment discontinuation were included in the analysis. Our review suggested that, due to the vague multiple-choice options for treatment discontinuation present in the CRF, different reasons were sometimes recorded for the same underlying reason for treatment discontinuation. Based on our review and analysis, we suggest an intermediate solution and a more systematic way to improve the current CRF for treatment discontinuations. Conclusion: This research provides insight and directions on how to optimize the CRF for recording treatment discontinuation. Further work needs to be done to build the learning into Clinical Data Interchange Standards Consortium standards.