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

PSI Introduction to Industry Training (ITIT) Course - 2025/2026

An introductory course giving an overview of the pharmaceutical industry and the drug development process as a whole, aimed at those with 1-3 years' experience. It comprises of six 2-day sessions covering a range of topics including Research and Development, Toxicology, Data Management and the Role of a CRO, Clinical Trials, Reimbursement, and Marketing.

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.

PSI Book Club Webinar: Atomic Habits - The Science of Getting Your Act Together

The book club’s usual focus is to read and discuss professional development books. In this short format event you can more easily develop you career without the commitment of reading the whole book - simply listen to the 1-hour long podcast before joining the interactive session on 21 May.

PSI Webinar: Methods and tools integrating clinical trial evidence with historical or real-world data, Bayesian borrowing, and causal inference

This webinar is organised by the RWD SIG and the Historical Data SIG. We will review recent methods, applications, and tools of integrating subject-level-data from clinical trial with external data using Bayesian methods and/or causal inference methods.

PSI Career Young Virtual Event (Q2 2025)

This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.

PSI Webinar: Applying the Estimand Framework to Clinical Pharmacology Trials with a Case Study in Bioequivalance

This will be a 45 minute webinar which will explain the topic presented in the published paper, ‘Applying the Estimand Framework to Clinical Pharmacology Trials with a Case Study in Bioequivalance’. There will be 15 minutes for a panel Q&A with some of the authors following the presentation.

PSI Webinar: Methodology and first results of the iRISE (improving Reproducibility In SciencE) consortium

This 1-hour webinar will be an opportunity to hear about the methodology and first results of the iRISE consortium. iRISE is working towards a better understanding of reproducibility and the interventions that work to improve it. At the end of the presentation there will also be the opportunity to ask questions.

One-day PSI/PHUSE Event: Change Management for Moving to R/Open-Source

This one-day event focuses on the comprehensive management of transitioning to R/Open-Source, addressing the challenges and providing actionable insights. Attendees will participate in sessions covering essential topics such as training best practices, creating strategic plans, making the case to senior management, and managing both statistical and programming aspects of the transition.

PSI Book Club - The Art of Explanation: How to Communicate with Clarity and Confidence

Develop your non-technical skills by reading The Art of Explanation by Ros Atkins and joining the Sept-Dec 2025 book club. You will be invited to join facilitated discussions of the concepts and ideas and apply skills from the book in-between sessions.

PSI Training Course: Pediatric Extrapolation

This course is aimed at biostatisticians with no or some pediatric drug development experience who are interested to further their understanding. We will give you an introduction to the pediatric drug development landscape. This will include identifying the key regulations and processes governing pediatric development, a discussion on the needs and challenges when conducting pediatric research and a focus on the ways to overcome these challenges from a statistical perspective.

PSI Career Young Virtual Event (Q3 2025)

This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.

PSI/EFSPI Vaccines Statistics Workshop

The program will feature insightful sessions led by distinguished invited speakers, alongside a poster session showcasing the latest advancements in the field. Further details will be provided.

PSI Career Young Virtual Event (Q4 2025)

This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.

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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