Fundamentals of Clinical Research: Bridging Medicine, Statistics and Operations

This book embraces the three pillars of clinical research: medicine, statistics and operations ('operations' is the logistics of research), and systematically covers the building blocks of a clinical study. The authors, a statistician and a physician, have many years of hands-on experience in the planning, conduct, analysis, interpretation and reporting of clinical trials. In writing this book, they had two main objectives. First, create a language and a logical flow of reasoning that, while precise and rigorous, are understandable to both the physician/biologist and the statistician. This common platform will help a constructive interaction between the two disciplines, which is absolutely crucial for good study plans to be generated. Second, do justice to operations, which is the discipline - and art - of making it all happen. Scientists often neglect operations and generate study plans which may be scientifically and methodologically brilliant, but fail miserably, because they are unfeasible in the real life settings where studies are conducted. Throughout the book the reader is confronted with the practical reality of clinical research.

The authors address 'classical' topics of clinical research, such as the choice of subjects and treatments, randomization and blinding, inference and statistical testing. At the same time they cover topics less commonly found in textbooks, such as the sources of variability of biological phenomena, a head to head comparison between the frequentist and the Bayesian approach to statistical testing, some useful but underused study designs (e.g. factorial and 'N of 1' designs), an overview of the drug development process from discovery topost-marketing surveillance. The emphasis is always on the rationale, the logic, the 'why'. Open questions are left open, with no attempt to offer simplistic solutions to controversial issues. This book has a practical approach, is full of examples and does not require any advanced mathematical knowledge. Nevertheless, it often goes beyond the elementary principles of experimental research. These features make it useful for biomedical researchers and statisticians alike.

About the Author:
Antonella Bacchieri as assistant professor at the Department of Statistical Sciences of the University of Padua