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

Joint PSI/EFSPI Visualisation SIG 'Wonderful Wednesday' Webinars

Our monthly webinar explores examples of innovative data visualisations relevant to our day to day work. Each month a new dataset is provided from a clinical trial or other relevant example, and participants are invited to submit a graphic that communicates interesting and relevant characteristics of the data.

AIMS SIG - Open-Source Lunch Bites

Topic: R Package Basics. Our monthly webinar series allows attendees to gain practical knowledge and skills in open-source coding and tools, with a focus on applications in the pharmaceutical industry. This month’s session, “R Package Basics,” will introduce the fundamentals of working with R packages—covering how to install, load, and manage them effectively to support data analysis and reproducible research. The session will provide a solid starting point, clarify common misconceptions, and offer valuable resources for continued learning.

PSI Mentoring 2026

Date: Ongoing 6 month cycle beginning late April/early May 2026 Are you a member of PSI looking to further your career or help develop others - why not sign up to the PSI Mentoring scheme? You can expand your network, improve your leadership skills and learn from more senior colleagues in the industry.

PSI Book Club Lunch and Learn: Communicating with Clarity and Confidence

If you have read Ros Atkins’ book The Art of Explanation or want to listen to the BBC’s ‘Communicator in Chief’, you are invited to join the PSI Book Club Lunch and Learn, to discuss the content and application with the author, Ros Atkins. Having written the book within the context of the news industry, Ros is keen to hear how we have applied the ideas as statisticians within drug development and clinical trials. There will be dedicated time during the webinar to ASK THE AUTHOR any questions – don’t miss out on this exclusive PSI Book Club event! Haven’t read the book yet? Pick up a copy today and join us. Explanation - identifying and communicating what we want to say - is described as an art, in the title of his book. However, the creativity comes from Ros’ discernment in identifying and describing a clear step-by-step process to follow and practice. Readers can learn Ros’ rules, developed and polished throughout his career as a journalist, to help communicate complex written or spoken information clearly.

PSI Training Course: Effective Leadership – the keys to growing your leadership capabilities

This course will consist of three online half-day workshops. The first will be aimed at building trust, the backbone of leadership and a key to becoming effective. This is key to building a solid foundation. The second will be on improving communication as a technical leader. This workshop will focus on communication strategies for different stakeholders and will involve tips on effective communication and how to develop the skills of active listening, coaching and what improv can teach us about good communication. The final workshop will bring these two components together to help leaders become more influential. This will also focus on how to use Steven Covey’s 7-Habits, in particular Habits 4, 5 and 6, which are called the habits of communication. The workshops will be interactive, allowing you to practice the concepts discussed. There will be plenty of time for questions and discussion. There will also be reflective time where you can think about what you are learning and how you might experiment with it.

Speaker	Biography	Abstract
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.
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.
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.
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.

Speaker	Biography	Abstract
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.
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.
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.
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.

Speaker	Biography	Abstract
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.
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.
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.
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.

Speaker	Biography	Abstract
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.
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.
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.
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.

Speaker	Biography	Abstract
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.
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.
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.
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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