Event

PSI Webinar: Hierarchical composite endpoints in clinical trials: challenges & opportunities

Date: Wednesday 23rd October 2024
Time: 14:00-16:00 BST | 15:00-17:00 CEST | 09:00-11:00 ET
Location: Online via Zoom
Speakers: Meg Gamalo (Pfizer), Cordula Zeller (Boehringer-Ingelheim), Patrick Schlömer (Bayer) and Dali Zhou (FDA)

Who is this event intended for? Statisticians with an interest in understanding the challenges and opportunities for hierarchical composite endpoints in drug development.
What is the benefit of attending? Learn about theory and application of hierarchical composite endpoints and their analysis methods (e.g., win ratio, win odds, net benefit) through presentations from statisticians in the industry and a regulatory discussant.

Registration

This event is free to both Members of PSI and Non-Members. To register your place for this event, please click here

Overview

This upcoming webinar will discuss the complexities and opportunities of clinical trials with hierarchical composite endpoints, covering topics such as win odds, win ratio, net benefit as well as regulatory considerations when defining hierarchical composite endpoints. We’ll start this webinar with a general introduction to hierarchical composite endpoints and an overview of common analysis methods including win ratio, win odds, and net benefit. Then, the practical considerations will be illustrated through case studies from clinical trials in heart failure and chronic kidney disease. We conclude with a discussion and a Q&A. Join us to gain valuable insights and a comprehensive understanding of this topic. 

Speaker details

Speaker

Biography Abstract

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Margaret (Meg) Gamalo

Margaret (Meg) Gamalo, PhD, is the Vice President and Statistics Head for Inflammation and Immunology at Pfizer Global Product Development. She brings extensive expertise in biostatistics, regulatory science, and clinical development across various disease areas in both adult and pediatric populations. Before joining Pfizer, she served as a Research Advisor in Global Statistical Sciences at Eli Lilly and Company and as a Mathematical Statistician at the Food and Drug Administration. As a Fellow of the American Statistical Association, she has led several industry initiatives, including scientific workgroups on Statistics in Pediatric Drug Development and the Statistical Perspective on AI/ML in Pharmaceutical Development within the Biopharmaceutical Section. She also chaired the Pediatric Innovation Task Force at the Biotechnology Innovation Organization and contributed to the European Forum for Good Clinical Practice– Children’s Medicine Working Party, which provided guidance on the inclusion of adolescents in adult research. She has held various positions in the Biopharmaceutical Section of the American Statistical Association and the Society for Clinical Trials. In addition to her leadership roles, Meg serves as the Editor-in-Chief of the Journal of Biopharmaceutical Statistics. She has authored over 70 peer-reviewed scientific publications in areas such as Bayesian methods, evidence synthesis, win statistics, causal inference, and pediatrics among others.

Introduction to composite endpoints and pairwise comparisons

This talk examines composite endpoints in clinical research, which combine multiple individual outcomes into a single measure to enhance efficiency and capture a more comprehensive assessment of treatment effects. While they offer advantages such as increased statistical power and streamlined data collection, composite endpoints can also introduce challenges related to interpretability and the potential masking of specific treatment effects. To address these disadvantages, win statistics emerge as a promising analytical approach by focusing on the proportion of wins versus losses across the composite outcomes. This framework not only preserves some of the advantages of composite endpoints but also provides an alternative interpretation of clinical trial results.

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Cordula Zeller

Cordula Zeller is a Clinical Data Scientist at Boehringer Ingelheim with more than 10 years experience in clinical trials in the Pharmaceutical Industry contributing to various projects in the area of Cardio-Metabolism.
She has been the lead statistician in the development program of empagliflozin in heart failure, which supported international submissions and worldwide approvals.
The development program included the EMPULSE trial, whose use of the win ratio as a primary endpoint was published and discussed in peer-reviewed articles.

The Win Ratio Method in Heart Failure Trials: Lessons from EMPULSE

In cardiovascular and specifically heart failure trials the win ratio method is discussed and used to combine mortality and morbidity data and evaluations of patient reported outcome data such as the Kansas City Cardiomyopathy Questionnaire (KCCQ).
The EMPULSE trial was conducted in patients with acute heart failure after initial stabilization and used a stratified win ratio as the primary endpoint. This endpoint included death, the number of heart failure events, time to first heart failure event and change from baseline in KCCQ-total symptom (TSS) score at 90 days.
This talk will discuss lessons learnt in terms of technical details such as stratification and multiple imputation as well as lessons learnt in the communication of results. 

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Patrick Schlömer

I am a Principal Statistician in late-stage cardiorenal development at Bayer AG, where I am currently acting as the Compound Statistician for the non-steroidal mineralocorticoid receptor antagonist finerenone and represent the statistical team on key internal and external committees to drive the strategic direction for the compound.
I hold a Bachelor of Science degree in Mathematics from the University of Oldenburg and a Master of Science degree in Medical Biometry and Biostatistics from the University of Bremen. I earned my Ph.D. in Statistics from the University of Bremen in 2014 for my work on group sequential and adaptive designs for three-arm 'gold standard' non-inferiority trials.
My methodological interests include adaptive designs, recurrent events, estimands and hierarchical composite endpoints. What I enjoy most about my work is presenting complex statistical concepts in a simple and entertaining manner, so that even non-statisticians can experience the joy of mathematics. I think this is an important prerequisite for the acceptance of novel statistical ideas by all stakeholders.

Gotta Catch ‘Em All – How to Capture All That Matters in Chronic Kidney Disease Trials?

Clinical trials in chronic kidney disease (CKD) often utilize composite endpoints comprising clinical events such as onset of dialysis or kidney transplantation along with a sustained large (e.g., ≥57%) decrease in glomerular filtration rate (GFR). Such events typically occur late in the disease course, resulting in large and long trials in which most participants do not contribute events. More recently, the rate of GFR decline over time (i.e. GFR slope) has been suggested as a more efficient endpoint, which is considered particularly useful in early CKD stages as well as patient populations with slower CKD progression.
This talk will present the use of hierarchical composite endpoints (HCEs) in clinical trials of CKD progression, emphasizing the ability to ‘capture’ all relevant information in a statistically elegant and clinically meaningful way. The application of this kidney HCE will be illustrated by post-hoc analyses of several large CKD trials.

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Dali Zhou

 Dali Zhou, Ph.D., is a senior mathematical statistician at the Office of Biostatistics/CDER/FDA. Dr. Zhou joined FDA in 2019 and has been supporting the clinical division of cardiology and nephrology, where he gained experience in the use of hierarchical composite endpoints in confirmatory analyses in clinical trials. Dr. Zhou also conducted research on the use of win ratio in clinical trials and presented in different conferences.

Regulatory advantages and challenges interpretation

Dali will be a discussant reflecting on the presentations above.


 

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