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With the critical role of statistics in the design, conduct,
analysis and reporting of clinical trials or observational studies
intended for regulatory purposes, numerous guidelines have been
issued by regulatory authorities around the world focusing on
statistical issues related to drug development. However, the
available literature on this important topic is sporadic, and often
not readily accessible to drug developers or regulatory personnel.
This book provides a systematic exposition of the interplay between
the two disciplines, including emerging themes pertaining to the
acceleration of the development of pharmaceutical medicines to
serve patients with unmet needs. Features: Regulatory and
statistical interactions throughout the drug development continuum
The critical role of the statistician in relation to the changing
regulatory and healthcare landscapes Statistical issues that
commonly arise in the course of drug development and regulatory
interactions Trending topics in drug development, with emphasis on
current regulatory thinking and the associated challenges and
opportunities The book is designed to be accessible to readers with
an intermediate knowledge of statistics, and can be a useful
resource to statisticians, medical researchers, and regulatory
personnel in drug development, as well as graduate students in the
health sciences. The authors' decades of experience in the
pharmaceutical industry and academia, and extensive regulatory
experience, comes through in the many examples throughout the book.
With ever-rising healthcare costs, evidence generation through
Health Economics and Outcomes Research (HEOR) plays an increasingly
important role in decision-making about the allocation of
resources. Accordingly, it is now customary for health technology
assessment and reimbursement agencies to request for HEOR evidence,
in addition to data from clinical trials, to inform decisions about
patient access to new treatment options. While there is a great
deal of literature on HEOR, there is a need for a volume that
presents a coherent and unified review of the major issues that
arise in application, especially from a statistical perspective.
Statistical Topics in Health Economics and Outcomes Research
fulfils that need by presenting an overview of the key analytical
issues and best practice. Special attention is paid to key
assumptions and other salient features of statistical methods
customarily used in the area, and appropriate and relatively
comprehensive references are made to emerging trends. The content
of the book is purposefully designed to be accessible to readers
with basic quantitative backgrounds, while providing an in-depth
coverage of relatively complex statistical issues. The book will
make a very useful reference for researchers in the pharmaceutical
industry, academia, and research institutions involved with HEOR
studies. The targeted readers may include statisticians, data
scientists, epidemiologists, outcomes researchers, health
economists, and healthcare policy and decision-makers.
With the critical role of statistics in the design, conduct,
analysis and reporting of clinical trials or observational studies
intended for regulatory purposes, numerous guidelines have been
issued by regulatory authorities around the world focusing on
statistical issues related to drug development. However, the
available literature on this important topic is sporadic, and often
not readily accessible to drug developers or regulatory personnel.
This book provides a systematic exposition of the interplay between
the two disciplines, including emerging themes pertaining to the
acceleration of the development of pharmaceutical medicines to
serve patients with unmet needs. Features: Regulatory and
statistical interactions throughout the drug development continuum
The critical role of the statistician in relation to the changing
regulatory and healthcare landscapes Statistical issues that
commonly arise in the course of drug development and regulatory
interactions Trending topics in drug development, with emphasis on
current regulatory thinking and the associated challenges and
opportunities The book is designed to be accessible to readers with
an intermediate knowledge of statistics, and can be a useful
resource to statisticians, medical researchers, and regulatory
personnel in drug development, as well as graduate students in the
health sciences. The authors' decades of experience in the
pharmaceutical industry and academia, and extensive regulatory
experience, comes through in the many examples throughout the book.
With ever-rising healthcare costs, evidence generation through
Health Economics and Outcomes Research (HEOR) plays an increasingly
important role in decision-making about the allocation of
resources. Accordingly, it is now customary for health technology
assessment and reimbursement agencies to request for HEOR evidence,
in addition to data from clinical trials, to inform decisions about
patient access to new treatment options. While there is a great
deal of literature on HEOR, there is a need for a volume that
presents a coherent and unified review of the major issues that
arise in application, especially from a statistical perspective.
Statistical Topics in Health Economics and Outcomes Research
fulfils that need by presenting an overview of the key analytical
issues and best practice. Special attention is paid to key
assumptions and other salient features of statistical methods
customarily used in the area, and appropriate and relatively
comprehensive references are made to emerging trends. The content
of the book is purposefully designed to be accessible to readers
with basic quantitative backgrounds, while providing an in-depth
coverage of relatively complex statistical issues. The book will
make a very useful reference for researchers in the pharmaceutical
industry, academia, and research institutions involved with HEOR
studies. The targeted readers may include statisticians, data
scientists, epidemiologists, outcomes researchers, health
economists, and healthcare policy and decision-makers.
Advancing the development, validation, and use of patient-reported
outcome (PRO) measures, Patient-Reported Outcomes: Measurement,
Implementation and Interpretation helps readers develop and enrich
their understanding of PRO methodology, particularly from a
quantitative perspective. Designed for biopharmaceutical
researchers and others in the health sciences community, it
provides an up-to-date volume on conceptual and analytical issues
of PRO measures. The book discusses key concepts relating to the
measurement, implementation, and interpretation of PRO measures. It
covers both introductory and advanced psychometric and
biostatistical methods for constructing and analyzing PRO measures.
The authors include many relevant real-life applications based on
their extensive first-hand experiences in the pharmaceutical
industry. They implement a wealth of simulated datasets to
illustrate concepts and heighten understanding based on practical
scenarios. For readers interested in conducting statistical
analyses of PRO measures and delving more deeply into the analytic
details, most chapters contain SAS code and output that illustrate
the methodology. Along with providing numerous references, the book
highlights current regulatory guidelines.
Advancing the development, validation, and use of patient-reported
outcome (PRO) measures, Patient-Reported Outcomes: Measurement,
Implementation and Interpretation helps readers develop and enrich
their understanding of PRO methodology, particularly from a
quantitative perspective. Designed for biopharmaceutical
researchers and others in the health sciences community, it
provides an up-to-date volume on conceptual and analytical issues
of PRO measures. The book discusses key concepts relating to the
measurement, implementation, and interpretation of PRO measures. It
covers both introductory and advanced psychometric and
biostatistical methods for constructing and analyzing PRO measures.
The authors include many relevant real-life applications based on
their extensive first-hand experiences in the pharmaceutical
industry. They implement a wealth of simulated datasets to
illustrate concepts and heighten understanding based on practical
scenarios. For readers interested in conducting statistical
analyses of PRO measures and delving more deeply into the analytic
details, most chapters contain SAS code and output that illustrate
the methodology. Along with providing numerous references, the book
highlights current regulatory guidelines.
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