Sample Size Calculations in Clinical Research

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Sample size calculation plays an important role in clinical research. It is not uncommon, however, to observe discrepancies among study objectives (or hypotheses), study design, statistical analysis (or test statistic), and sample size calculation. Focusing on sample size calculation for studies conducted during the various phases of clinical research and development, Sample Size Calculation in Clinical Research explores the causes of discrepancies and how to avoid them.

This volume provides formulas and procedures for determination of sample size required not only for testing equality, but also for testing non-inferiority/superiority, and equivalence (similarity) based on both untransformed (raw) data and log-transformed data under a parallel-group design or a crossover design with equal or unequal ratio of treatment allocations. It contains a comprehensive and unified presentation of statistical procedures for sample size calculation that are commonly employed at various phases of clinical development. Each chapter includes, whenever possible, real examples of clinical studies from therapeutic areas such as cardiovascular, central nervous system, anti-infective, oncology, and women's health to demonstrate the clinical and statistical concepts, interpretations, and their relationships and interactions.

The book highlights statistical procedures for sample size calculation and justification that are commonly employed in clinical research and development. It provides clear, illustrated explanations of how the derived formulas and/or statistical procedures can be used.
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About the author

SHEIN-CHUNG CHOW, PhD, is currently Vice President of Biostatistics and Clinical Data Management for Millennium Pharmaceuticals, Inc., in Cambridge, Massachusetts.

JEN-PEI LIU, PhD, is currently Professor of Statistics for the National Cheng kung University in Tainan, Taiwan, and an investigator for the National Health Research Institutes in Taipei, Taiwan. Both authors have extensive background experience in industry and academia, and, collectively, have published well over a dozen books in their respective fields of study.

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Additional Information

Publisher
CRC Press
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Published on
Mar 4, 2003
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Pages
358
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ISBN
9780203911341
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Best For
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Language
English
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Genres
Mathematics / Probability & Statistics / General
Medical / Biostatistics
Medical / Epidemiology
Medical / Pharmacology
Medical / Research
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Content Protection
This content is DRM protected.
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Eligible for Family Library

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Shein-Chung Chow
The US Food and Drug Administration's Report to the Nation in 2004 and 2005 indicated that one of the top reasons for drug recall was that stability data did not support existing expiration dates. Pharmaceutical companies conduct stability studies to characterize the degradation of drug products and to estimate drug shelf life. Illustrating how stability studies play an important role in drug safety and quality assurance, Statistical Design and Analysis of Stability Studies presents the principles and methodologies in the design and analysis of stability studies.

After introducing the basic concepts of stability testing, the book focuses on short-term stability studies and reviews several methods for estimating drug expiration dating periods. It then compares some commonly employed study designs and discusses both fixed and random batch statistical analyses. Following a chapter on the statistical methods for stability analysis under a linear mixed effects model, the book examines stability analyses with discrete responses, multiple components, and frozen drug products. In addition, the author provides statistical methods for dissolution testing and explores current issues and recent developments in stability studies.

To ensure the safety of consumers, professionals in the field must carry out stability studies to determine the reliability of drug products during their expiration period. This book provides the material necessary for you to perform stability designs and analyses in pharmaceutical research and development.
James E. De Muth
Shein-Chung Chow
Praise for the Second Edition:

"... this is a useful, comprehensive compendium of almost every possible sample size formula. The strong organization and carefully defined formulae will aid any researcher designing a study."

-Biometrics

"This impressive book contains formulae for computing sample size in a wide range of settings. One-sample studies and two-sample comparisons for quantitative, binary, and time-to-event outcomes are covered comprehensively, with separate sample size formulae for testing equality, non-inferiority, and equivalence. Many less familiar topics are also covered ..." – Journal of the Royal Statistical Society

Sample Size Calculations in Clinical Research, Third Edition presents statistical procedures for performing sample size calculations during various phases of clinical research and development. A comprehensive and unified presentation of statistical concepts and practical applications, this book includes a well-balanced summary of current and emerging clinical issues, regulatory requirements, and recently developed statistical methodologies for sample size calculation.

Features:

Compares the relative merits and disadvantages of statistical methods for sample size calculations

Explains how the formulae and procedures for sample size calculations can be used in a variety of clinical research and development stages

Presents real-world examples from several therapeutic areas, including cardiovascular medicine, the central nervous system, anti-infective medicine, oncology, and women’s health

Provides sample size calculations for dose response studies, microarray studies, and Bayesian approaches

This new edition is updated throughout, includes many new sections, and five new chapters on emerging topics: two stage seamless adaptive designs, cluster randomized trial design, zero-inflated Poisson distribution, clinical trials with extremely low incidence rates, and clinical trial simulation.

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Book 83
A Western-Based Approach to Analyzing TCMs

In recent years, many pharmaceutical companies and clinical research organizations have been focusing on the development of traditional Chinese (herbal) medicines (TCMs) as alternatives to treating critical or life-threatening diseases and as pathways to personalized medicine.

Quantitative Methods for Traditional Chinese Medicine Development is the first book entirely devoted to the design and analysis of TCM development from a Western perspective, i.e., evidence-based clinical research and development. The book provides not only a comprehensive summary of innovative quantitative methods for developing TCMs but also a useful desk reference for principal investigators involved in personalized medicine.

Written by one of the world’s most prominent biostatistics researchers, the book connects the pharmaceutical industry, regulatory agencies, and academia. It presents a state-of-the-art examination of the subject for:

Scientists and researchers who are engaged in pharmaceutical/clinical research and development of TCMs Those in regulatory agencies who make decisions in the review and approval process of TCM regulatory submissions Biostatisticians who provide statistical support to assess clinical safety and effectiveness of TCMs and related issues regarding quality control and assurance as well as to test for consistency in the manufacturing processes for TCMs

This book covers all of the statistical issues encountered at various stages of pharmaceutical/clinical development of a TCM. It explains regulatory requirements; product specifications and standards; and various statistical techniques for evaluation of TCMs, validation of diagnostic procedures, and testing consistency. It also contains an entire chapter of case studies and addresses critical issues in TCM development and FAQs from a regulatory perspective.

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