New Developments in Statistical Analysis of Clinical Trials for New Drugs

Author: Su Binghua, Editor-in-Chief
Publisher:
Publishing Date: 2000-08-01
Features: The author has been studying and participating in clinical trials in Europe for over three years and is familiar with the regulations on clinical trials in Europe and America. After returning to China in August 1996, he served as a drug evaluation expert for the Ministry of Health and the National Drug Administration. Under the leadership of the New Drug Evaluation Center, he participated in many domestic and international clinical trials and statistical analysis work, accumulating extensive experience. In participating in the drafting of the national guidelines for biostatistics in clinical trials and the technical work related to traditional Chinese medicine clinical trials, he became more familiar with and mastered China's various laws and regulations. He deeply felt that to improve the level of new drug clinical trials in China and ensure the safety and efficacy of medications for the people, efforts must be focused on standardization and scientific rigor. Therefore, he compiled this work. The preliminary draft of this book was completed in the UK in 1996, and it has recently been supplemented and rewritten, especially Chapter on the Regulations for Clinical Research of New Drugs in China. Sections 4–10 of this chapter are the author's summarized findings from practical work, benefiting from the guidance and assistance of leaders and staff of the National Drug Administration, as well as the guidance of domestic medical experts with rich experience in new drug clinical trials. Most statistical analyses in China's new drug clinical trials still remain at the very basic level, such as t-tests, χ2-tests, and RIDIT analysis. These basic parts can be found in relevant textbooks in China, for example, the book "Medical Statistics and its Software Package" written by the author himself. Therefore, this book omits these basic parts. However, the statistical models used in recent years abroad, which the author refers to as "new developments in statistical analysis," are rarely or not mentioned at all in domestic books. The author has dedicated effort to this aspect, referencing many recent English reference books to write this book. Chapter 2 introduces dozens of sample size estimation methods, while Chapters 3, 4, and 5 introduce various statistical models used in clinical trials. Chapters 6, 7, and 8 discuss statistical models in epidemiological research. Chapter 6 covers the basic part, Chapter 7 focuses on Logistic regression, and Chapter 8 focuses on survival data analysis, all to guide the correct use of statistical analysis methods in China's new drug clinical trials. All examples and exercises in this book are derived from actual data in medical new drug clinical trials. To preserve the original meaning, references are listed, and as much English terminology as possible is retained, with statistical English vocabulary included in the book. This book uses the SAS (Statistical Analysis System) statistical software package as the statistical tool. All examples and exercises provide SAS programs and their main computational results to guide professionals in China's new drug clinical trials to correctly use SAS software for statistical analysis.
The target readers of New Developments in Statistical Analysis for New Drug Clinical Trials are professionals at all levels engaged in new drug research and clinical trials. It provides operational procedures for new drug clinical trials and many effective statistical analysis methods, serving as a reference book for professional workers and related personnel. Given that China's new drug clinical trial work is still in its initial stages and many aspects need to be gradually improved, the publication of this book aims to play a role in paving the way. By seriously learning from international advanced experiences and continuously enriching and perfecting them in practice, it is hoped that China can soon align with international standards. This requires the joint efforts of all stakeholders to achieve this goal.