Statistical Design, Monitoring, and Analysis of Clinical Trials: Principles and Methods, 2/e (Hardcover)

Statistical Design and Analysis of Clinical Trials, Second Edition concentrates on the biostatistics component of clinical trials. This new edition is updated throughout and includes five new chapters.

Developed from the authors' courses taught to public health and medical students, residents, and fellows during the past 15 years, the text shows how biostatistics in clinical trials is an integration of many fundamental scientific principles and statistical methods. The book begins with ethical and safety principles, core trial design concepts, the principles and methods of sample size and power calculation, and analysis of covariance and stratified analysis. It then focuses on sequential designs and methods for two-stage Phase II cancer trials to Phase III group sequential trials, covering monitoring safety, futility, and efficacy. The authors also discuss the development of sample size reestimation and adaptive group sequential procedures, explain the concept of different missing data processes, and describe how to analyze incomplete data by proper multiple imputations.

This text reflects the academic research, commercial development, and public health aspects of clinical trials. It gives students a multidisciplinary understanding of the concepts and techniques involved in designing and analyzing various types of trials. The book's balanced set of homework assignments and in-class exercises are appropriate for students in (bio)statistics, epidemiology, medicine, pharmacy, and public health.

《臨床試驗的統計設計與分析，第二版》專注於臨床試驗的生物統計學部分。這本新版書籍在全書中進行了更新，並新增了五個新章節。

本書是根據作者在過去15年中教授給公共衛生和醫學學生、住院醫師和研究員的課程所發展而成，展示了臨床試驗中的生物統計學是許多基本科學原理和統計方法的整合。該書首先介紹了倫理和安全原則、核心試驗設計概念、樣本大小和功效計算的原則和方法，以及共變數分析和分層分析。然後，重點介紹了序列設計和兩階段II期癌症試驗到III期群組序列試驗的方法，包括監測安全性、無效性和效力。作者還討論了樣本大小重新估計和自適應群組序列程序的發展，解釋了不同缺失數據過程的概念，並描述了如何通過適當的多重插補方法分析不完整數據。

本書反映了臨床試驗的學術研究、商業發展和公共衛生方面。它使學生能夠多學科地理解設計和分析各種類型試驗的概念和技術。書中平衡的家庭作業和課堂練習適合（生物）統計學、流行病學、醫學、藥學和公共衛生學的學生。

Weichung Joe Shih, PhD, has been tenured professor and chair of the Department of Biostatistics, Rutgers School of Public Health, Rutgers University, New Brunswick, New Jersey, and director of Biometrics Division at the Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey. He is an elected fellow of the American Statistical Association (1996) and an elected member of the International Statistical Institute (2001). Prior to joining academia, he spent his formative years (1982-1999) at Merck Research Laboratories, Rahway, New Jersey. He served in the Advisory Board of the US FDA for reviewing new drug applications, and was associate editor of professional journals, including　Statistics in Medicine,　Controlled Clinical Trials,　Clinical Cancer Research,　Statistics in Biopharmaceutical Research, and　Statistics in Bioscience. He pioneered in the field of sample size re-estimation for clinical trials, which has evolved into the field of adaptive designs. He also first advocated the use of consistency criterion for international bridging studies, which is now adopted by the ICH guidance for global multiregional clinical trials. He has collaborated extensively with physicians in various therapeutic areas and authored numerous papers in statistical methodology in clinical trials. His research interests include adaptive designs and missing data issues. He has been honored as professor emeritus of Rutgers University since July 2019.

Joseph Aisner, MD, is a professor of medicine and a professor of environmental and occupational medicine at the Robert Wood Johnson Medical School of Rutgers University, New Brunswick, New Jersey, director of Medical Oncology Unit at the Robert Wood Johnson University Hospital, New Brunswick, New Jersey, and co-leader of the Clinical Investigations Program at the Rutgers Cancer Institute of New Jersey. He has published extensively and has served on the editorial board of multiple journals, including Journal of Clinical Oncology, Cancer Therapeutics, Medical Oncology, Clinical Cancer Research, and Hematology-Oncology Today. He is a fellow of the American College of Physicians and the American Society of Clinical Oncology. He serves on and chairs several National Data Monitoring Committees, has served on multiple National Institutes of Health (NIH) Study Sections, and has headed two National Cooperative Cancer Study Groups. His research interests include cancer clinical trials and evaluation of therapeutic interventions.

魏忠（Weichung）·喬·施（Shih）博士是羅格斯大學（Rutgers University）公共衛生學院（Rutgers School of Public Health）生物統計學系（Department of Biostatistics）的終身教授和系主任，同時也是羅格斯癌症研究所（Rutgers Cancer Institute of New Jersey）生物統計學部門（Biometrics Division）的主任。他是美國統計學會（American Statistical Association）的當選會士（1996年）和國際統計學會（International Statistical Institute）的當選會員（2001年）。在加入學術界之前，他在紐澤西州拉赫韋（Rahway）的默克研究實驗室（Merck Research Laboratories）度過了他的成長歲月（1982年至1999年）。他曾在美國食品藥品監督管理局（US FDA）的諮詢委員會擔任審查新藥申請的職務，並擔任專業期刊的副編輯，包括《Statistics in Medicine》、《Controlled Clinical Trials》、《Clinical Cancer Research》、《Statistics in Biopharmaceutical Research》和《Statistics in Bioscience》。他在臨床試驗的樣本量重新估計領域開創了先河，這一領域已發展成為自適應設計的領域。他還首次提倡在國際橋接研究中使用一致性準則，這一準則現已被國際藥品管理局（ICH）的全球多區域臨床試驗指南所採納。他與各個治療領域的醫生進行了廣泛的合作，並在臨床試驗的統計方法學方面撰寫了大量論文。他的研究興趣包括自適應設計和缺失數據問題。自2019年7月起，他榮獲羅格斯大學名譽教授的稱號。

約瑟夫·艾斯納（Joseph Aisner）醫學博士是羅伯特·伍德·約翰遜醫學院（Robert Wood Johnson Medical School）的醫學教授和環境與職業醫學教授，同時也是羅伯特·伍德·約翰遜大學醫院（Robert Wood Johnson University Hospital）醫學腫瘤學單位（Medical Oncology Unit）的主任，以及羅格斯癌症研究所（Rutgers Cancer Institute of New Jersey）臨床調查計劃（Clinical Investigations Program）的聯合負責人。他發表了大量論文，並擔任多個期刊的編輯委員會成員，包括《Journal of Clinical Oncology》、《Cancer Therapeutics》、《Medical Oncology》、《Clinical Cancer Research》和《Hematology-Oncology Today》。他是美國內科醫師學會（American College of Physicians）和美國臨床腫瘤學會（American Society of Clinical Oncology）的會士。他擔任並主持了多個國家數據監測委員會，曾參與多個美國國立衛生研究院（NIH）的研究部門，並領導了兩個國家合作癌症研究小組。他的研究興趣包括癌症臨床試驗和治療干預的評估。