Marc Buyse holds a ScD in biostatistics from the Harvard School of Public Health, Boston, MA. He is Associate Professor of Biostatistics at U Hasselt, Belgium, and the founder of companies providing statistical services and software to the biopharmaceutical industry: International Drug Development Institute (IDDI), CluePoints and One2Treat.Johan Verbeeck trained as a biotechnologist and biostatistician and transitioned from the pharmaceutical industry to academia. Currently, he serves as a post-doctoral biostatistical researcher at the Data Science Institute at U Hasselt, Belgium, specializing in statistical methods for analyzing multivariate outcomes, especially in small sample trials and cardiology.Mickael De Backer received a PhD in biostatistics from UCLouvain, Belgium, in 2018, with a dissertation focused on quantile regressions in survival analysis. Since then, his work and research have centered on generalized pairwise comparisons in both academic and industry settings. He also serves as an invited lecturer in biostatistics at UCLouvain.Vaiva Deltuvaite-Thomas obtained a PhD in biostatistics from U Hasselt, Belgium, after working as a community pharmacist in Lithuania, Belgium, Ireland, and France, which made her acutely aware of the need to understand and explain treatment-related information to patients. She is currently providing consultancy services as statistical scientist at International Drug Development Institute (IDDI).Everardo D. Saad trained and practiced as a medical oncologist before shifting his career to clinical research and education. He serves as Medical Director at International Drug Development Institute (IDDI), Belgium, and is the founder of Dendrix, a medical education and research company in Sao Paulo, Brazil.Geert Molenberghs received a PhD in biostatistics from U Antwerpen, Belgium. He was President of the International Biometric Society. He is Fellow of the American Statistical Association. He is Professor and founding director of the Center for Statistics at U Hasselt and of the Interuniversity Institute for Biostatistics and statistical Bioinformatics (U Hasselt and KU Leuven).

• Abbreviations Foreword Preface Editors Contributors Part I. Introduction 1. Generalized Pairwise Comparisons for patient-centric treatment decisions Part II. Statistical Theory 2. Measures of Treatment Effect 3. Inference 4. Right-censored Data 5. Restricted GPC Statistics 6. Missing Data 7. Challenges and Limitations of NTB Part III. Advanced Topics 8. GPC and Rank Procedures 9. Stratification and non-parametric adjustment 10. Covariate adjustment for GPC 11. Cure Rate Models 12. Group Sequential Designs 13. The Desirability Of Outcome Ranking (DOOR) 14. Theoretical Properties of GPC Statistics Part IV. Software and Datasets 15. Illustrating GPC through a graphical user interface 16. GPC through a command line interface Part V. Applications 17. Cardiovascular Disease 18. Oncology 19. Rare Diseases 20. Regulatory considerations for GPC analyses 21. Quantitative benefit-risk assessment Part VI. Patient-centricity 22. GPC for N − of − 1 Trials 23. Elicitation of Patient Preferences for GPC 24. Shared Decision-Making 25. Patient centricity and participation 26. Open Science and Patient-level Data Sharing Postface Bibliography Index

“This book stands as a guiding beacon for developers, researchers, and regulators, sparking the evolution of fit-for-dossier trials into agile studies tailored for informed decisions.” Francesco Pignatti, Head of the Office of Oncology and Haematology, European Medicines Agency, Amsterdam, the Netherlands.“The editors of this book and the chapter authors are to be commended for consolidating the considerable advances in GPC statistical methods into a single comprehensive resource that should serve as a standard for many years to come.” Gene Pennello, Mathematical Statistician, US Food and Drug Administration, Bethesda, MD.

Marc Buyse holds a ScD in biostatistics from the Harvard School of Public Health, Boston, MA. He is Associate Professor of Biostatistics at U Hasselt, Belgium, and the founder of companies providing statistical services and software to the biopharmaceutical industry: International Drug Development Institute (IDDI), CluePoints and One2Treat.Johan Verbeeck trained as a biotechnologist and biostatistician and transitioned from the pharmaceutical industry to academia. Currently, he serves as a post-doctoral biostatistical researcher at the Data Science Institute at U Hasselt, Belgium, specializing in statistical methods for analyzing multivariate outcomes, especially in small sample trials and cardiology.Mickael De Backer received a PhD in biostatistics from UCLouvain, Belgium, in 2018, with a dissertation focused on quantile regressions in survival analysis. Since then, his work and research have centered on generalized pairwise comparisons in both academic and industry settings. He also serves as an invited lecturer in biostatistics at UCLouvain.Vaiva Deltuvaite-Thomas obtained a PhD in biostatistics from U Hasselt, Belgium, after working as a community pharmacist in Lithuania, Belgium, Ireland, and France, which made her acutely aware of the need to understand and explain treatment-related information to patients. She is currently providing consultancy services as statistical scientist at International Drug Development Institute (IDDI).Everardo D. Saad trained and practiced as a medical oncologist before shifting his career to clinical research and education. He serves as Medical Director at International Drug Development Institute (IDDI), Belgium, and is the founder of Dendrix, a medical education and research company in Sao Paulo, Brazil.Geert Molenberghs received a PhD in biostatistics from U Antwerpen, Belgium. He was President of the International Biometric Society. He is Fellow of the American Statistical Association. He is Professor and founding director of the Center for Statistics at U Hasselt and of the Interuniversity Institute for Biostatistics and statistical Bioinformatics (U Hasselt and KU Leuven).

• Abbreviations Foreword Preface Editors Contributors Part I. Introduction 1. Generalized Pairwise Comparisons for patient-centric treatment decisions Part II. Statistical Theory 2. Measures of Treatment Effect 3. Inference 4. Right-censored Data 5. Restricted GPC Statistics 6. Missing Data 7. Challenges and Limitations of NTB Part III. Advanced Topics 8. GPC and Rank Procedures 9. Stratification and non-parametric adjustment 10. Covariate adjustment for GPC 11. Cure Rate Models 12. Group Sequential Designs 13. The Desirability Of Outcome Ranking (DOOR) 14. Theoretical Properties of GPC Statistics Part IV. Software and Datasets 15. Illustrating GPC through a graphical user interface 16. GPC through a command line interface Part V. Applications 17. Cardiovascular Disease 18. Oncology 19. Rare Diseases 20. Regulatory considerations for GPC analyses 21. Quantitative benefit-risk assessment Part VI. Patient-centricity 22. GPC for N − of − 1 Trials 23. Elicitation of Patient Preferences for GPC 24. Shared Decision-Making 25. Patient centricity and participation 26. Open Science and Patient-level Data Sharing Postface Bibliography Index

“This book stands as a guiding beacon for developers, researchers, and regulators, sparking the evolution of fit-for-dossier trials into agile studies tailored for informed decisions.” Francesco Pignatti, Head of the Office of Oncology and Haematology, European Medicines Agency, Amsterdam, the Netherlands.“The editors of this book and the chapter authors are to be commended for consolidating the considerable advances in GPC statistical methods into a single comprehensive resource that should serve as a standard for many years to come.” Gene Pennello, Mathematical Statistician, US Food and Drug Administration, Bethesda, MD.

Marc Buyse holds a ScD in biostatistics from the Harvard School of Public Health, Boston, MA. He is Associate Professor of Biostatistics at U Hasselt, Belgium, and the founder of companies providing statistical services and software to the biopharmaceutical industry: International Drug Development Institute (IDDI), CluePoints and One2Treat.Johan Verbeeck trained as a biotechnologist and biostatistician and transitioned from the pharmaceutical industry to academia. Currently, he serves as a post-doctoral biostatistical researcher at the Data Science Institute at U Hasselt, Belgium, specializing in statistical methods for analyzing multivariate outcomes, especially in small sample trials and cardiology.Mickael De Backer received a PhD in biostatistics from UCLouvain, Belgium, in 2018, with a dissertation focused on quantile regressions in survival analysis. Since then, his work and research have centered on generalized pairwise comparisons in both academic and industry settings. He also serves as an invited lecturer in biostatistics at UCLouvain.Vaiva Deltuvaite-Thomas obtained a PhD in biostatistics from U Hasselt, Belgium, after working as a community pharmacist in Lithuania, Belgium, Ireland, and France, which made her acutely aware of the need to understand and explain treatment-related information to patients. She is currently providing consultancy services as statistical scientist at International Drug Development Institute (IDDI).Everardo D. Saad trained and practiced as a medical oncologist before shifting his career to clinical research and education. He serves as Medical Director at International Drug Development Institute (IDDI), Belgium, and is the founder of Dendrix, a medical education and research company in Sao Paulo, Brazil.Geert Molenberghs received a PhD in biostatistics from U Antwerpen, Belgium. He was President of the International Biometric Society. He is Fellow of the American Statistical Association. He is Professor and founding director of the Center for Statistics at U Hasselt and of the Interuniversity Institute for Biostatistics and statistical Bioinformatics (U Hasselt and KU Leuven).

• Abbreviations Foreword Preface Editors Contributors Part I. Introduction 1. Generalized Pairwise Comparisons for patient-centric treatment decisions Part II. Statistical Theory 2. Measures of Treatment Effect 3. Inference 4. Right-censored Data 5. Restricted GPC Statistics 6. Missing Data 7. Challenges and Limitations of NTB Part III. Advanced Topics 8. GPC and Rank Procedures 9. Stratification and non-parametric adjustment 10. Covariate adjustment for GPC 11. Cure Rate Models 12. Group Sequential Designs 13. The Desirability Of Outcome Ranking (DOOR) 14. Theoretical Properties of GPC Statistics Part IV. Software and Datasets 15. Illustrating GPC through a graphical user interface 16. GPC through a command line interface Part V. Applications 17. Cardiovascular Disease 18. Oncology 19. Rare Diseases 20. Regulatory considerations for GPC analyses 21. Quantitative benefit-risk assessment Part VI. Patient-centricity 22. GPC for N − of − 1 Trials 23. Elicitation of Patient Preferences for GPC 24. Shared Decision-Making 25. Patient centricity and participation 26. Open Science and Patient-level Data Sharing Postface Bibliography Index

“This book stands as a guiding beacon for developers, researchers, and regulators, sparking the evolution of fit-for-dossier trials into agile studies tailored for informed decisions.” Francesco Pignatti, Head of the Office of Oncology and Haematology, European Medicines Agency, Amsterdam, the Netherlands.“The editors of this book and the chapter authors are to be commended for consolidating the considerable advances in GPC statistical methods into a single comprehensive resource that should serve as a standard for many years to come.” Gene Pennello, Mathematical Statistician, US Food and Drug Administration, Bethesda, MD.