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

PSI Careers - MEDMathS: Medicine Empowered by Data, Maths and Statistics

Date: Wednesday 6th November 2024 A careers talk about medical statistics and how it plays a crucial role in developing new medicines

Joint PSI/EFSPI Visualisation SIG 'Wonderful Wednesday' Webinars

Date: The Second Wednesday of every Month 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.

Joint PSI/EFSPI Causal Inference SIG Webinar: Opportunities in applying a causal inference framework during the analysis of an RCT

Date: Tuesday 19th November 2024 This webinar will discuss opportunities in applying causal inference methodology during the analysis of RCT data.

PSI Training Course: Introduction to Bayesian Methods

Dates: Module 1 - Wednesday 20th November Module 2 - Tuesday 26th November Module 3 - Thursday 28th November This interactive and hands on online course, aimed at beginner Bayesians who have little or no experience in Bayesian statistics, is split into 3 modules. Module 1 introduces Bayesian concepts and looks at how Bayes has been used recently in the Pharmaceutical Industry, and participants will undertake their own data collection exercise in order to analyse a simple Bayesian trial. Module 2 takes a look at the concepts of Bayesian statistics and key terminology and provides a chance to analyse some data using a simple Bayesian approach. Module 3 takes a further look at the use of Bayesian statistics in drug development and regulatory requirements and digs deeper into analysis issues.

PSI Medical Statistics Student Careers Event 2024

Date: 20 October 2024 This event is aimed at students with an interest in the field of Medical Statistics, for example within pharmaceuticals, healthcare and/or medical research.

PSI Vaccines SIG Webinar: Statistical designs for assessment of vaccine safety in pregnancy

Date: Wednesday 20th November 2024 This is a webinar on the design of studies to assess safety of vaccines administered in pregnancy.

Joint PSI/EFSPI Pre-Clinical SIG Webinar: Virtual Control Groups in Toxicity Studies

Date: Re-scheduled to Tuesday 26th November 2024 Lea Vaas will present how replacement of concurrent control animals by Virtual Control Groups (VCGs) in systemic toxicity studies may help in contributing to the 3R's principle of animal experimentation: Reduce, Refine, Replace.

PSI Book Club Webinar: 7 Habits You Wish You Had (But Probably Don't)

Date: Wednesday 27th November 2024 The 7 Habits of Highly Effective People has had a profound impact on millions of people around the world. The book focuses on cultivating character and refining personality. Its principles are not only transformative for personal growth but also serve as powerful tools for professional development. Over the past few months, members of the PSI Book Club have been exploring these transformative principles through focused discussions and real-world applications. These principles aren’t just theories—they are actionable strategies that can be integrated into your daily life to drive meaningful change. In this upcoming session, we’ll bring these discussions to a broader audience. Together, we’ll explore how to practically apply the 7 Habits in our professional lives, share key insights from our book club sessions, and reflect on how these timeless principles can enhance both our personal and professional journeys.

PSI Career Young Virtual Event (Q4 2024)

Date: Tuesday 10th December 2024 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 Journal Club: Group Sequential Designs

Date: Thursday 12th December 2024 Chaired by Jenny Devenport, join us to hear Andy Grieve and Zhiwei Zhang discuss their recent work on group sequential designs.

PSI Introduction to Industry Training (ITIT) Course - 2024/2025

Date: October 2024 - July 2025 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.

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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