This chapter explores the critical role of survival analysis in assessing adverse events during clinical trials, focusing on the nuances of censored data and various estimation methodologies. It critically examines common approaches like the Kaplan-Meier estimator, highlighting their limitations and biases in the context of competing events. The discussion draws from a comprehensive analysis of trials to underscore the importance of accurate methodologies for reliable safety assessments in clinical practice.
✔ How differing follow-up times and censoring bias AE results.
✔ The role of the Aalen–Johansen estimator and why it should be standard practice.
✔ What the SAVVY collaboration achieved by uniting pharma, academia, and regulators.
✔ Real-world examples of how safety analyses can dramatically change the interpretation of treatment risk.
✔ Lessons on collaboration, methodology, and change management in the pharma industry.
Why You Should Listen:
Adverse events are a critical part of any trial, yet they’re often analyzed using simplistic methods that can mislead decision-makers. This episode will help you:
Gain insights you can apply immediately to your own projects to improve the accuracy and credibility of your analyses.
Understand the hidden biases in traditional AE analysis.
Learn how to align safety and efficacy assessments for a fairer benefit–risk evaluation.
Discover the power of collaboration between pharma, academia, and regulators through the SAVVY project.
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🔗 My New Book: How to Be an Effective Statistician - Volume 1– It’s packed with insights to help statisticians, data scientists, and quantitative professionals excel as leaders, collaborators, and change-makers in healthcare and medicine.
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