Handbook of Generalized Pairwise Comparisons (eBook, PDF)

Methods for Patient-Centric Analysis
Redaktion: Buyse, Marc; Molenberghs, Geert; Deltuvaite-Thomas, Vaiva; Backer, Mickaël de; Saad, Everardo D.; Verbeeck, Johan

• Format: PDF

Produktbeschreibung

In today's healthcare landscape, there is a pressing need for quantitative methodologies that include the patients' perspective in any treatment decision.

Handbook of Generalized Pairwise Comparisons: Methods for Patient-Centric Analysis provides a comprehensive overview of an innovative and powerful statistical methodology that generalizes the traditional Wilcoxon-Mann-Whitney test by extending it to any number of outcomes of any type and including thresholds of clinical relevance into a single, multidimensional evaluation.

The book covers the statistical foundations of generalized pairwise comparisons (GPC), applications in various disease areas, implications for regulatory approvals and benefit-risk analyses, and considerations for patient-centricity in clinical research. With contributions from leading experts in the field, this book stands as an essential resource for a more holistic and patient-centric assessment of treatment effects.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 582
• Erscheinungstermin: 31. März 2025
• Englisch
• ISBN-13: 9781040319178
• Artikelnr.: 72859777

Autorenporträt

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).

Rezensionen

"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.