This book provides a comprehensive introduction to statistical methods for designing early phase dose-finding clinical trials. It will serve as a textbook or handbook for graduate students and practitioners in biostatistics and clinical investigators who are involved in designing, conducting, monitoring, and analyzing dose-finding trials. The book will also provide an overview of advanced topics and discussions in this field for the benefit of researchers in biostatistics and statistical science. Beginning with backgrounds and fundamental notions on dose finding in early phase clinical trials, the book then provides traditional and recent dose-finding designs of phase I trials for, e.g., cytotoxic agents in oncology, to evaluate toxicity outcome. Included are rule-based and model-based designs, such as 3 + 3 designs, accelerated titration designs, toxicity probability interval designs, continual reassessment method and related designs, and escalation overdose control designs. This book also covers more complex and updated dose-finding designs of phase I-II and I/II trials for cytotoxic agents, and cytostatic agents, focusing on both toxicity and efficacy outcomes, such as designs with covariates and drug combinations, maximum tolerated dose-schedule finding designs, and so on.
This book deals with advanced methods for adaptive phase I dose-finding clinical trials for combination of two agents and molecularly targeted agents (MTAs) in oncology. It provides not only methodological aspects of the dose-finding methods, but also software implementations and practical considerations in applying these complex methods to real cancer clinical trials. Thus, the book aims to furnish researchers in biostatistics and statistical science with a good summary of recent developments of adaptive dose-finding methods as well as providing practitioners in biostatistics and clinical investigators with advanced materials for designing, conducting, monitoring, and analyzing adaptive dose-finding trials. The topics in the book are mainly related to cancer clinical trials, but many of those topics are potentially applicable or can be extended to trials for other diseases. The focus is mainly on model-based dose-finding methods for two kinds of phase I trials. One is clinical trials with combinations of two agents. Development of dose-finding methods for two-agent combination trials requires reasonable models that can adequately capture joint toxicity probabilities for two agents, taking into consideration possible interactions of the two agents on toxicity probability such as synergistic or antagonistic effects. Another is clinical trials for evaluating both efficacy and toxicity outcomes in single- and two-agent combination trials. These methods are often applied to the phase I trials including MTAs because the toxicity and efficacy for a MTA does not monotonically increase with dose, but the efficacy often increases initially with the dose and then plateaus. Successful software implementations for several dose-finding methods are introduced in the book, and their operating characteristics in practice are discussed. Recent advance of the adaptive dose-finding methods in drug developments are also provided.
This book deals with advanced methods for adaptive phase I dose-finding clinical trials for combination of two agents and molecularly targeted agents (MTAs) in oncology. It provides not only methodological aspects of the dose-finding methods, but also software implementations and practical considerations in applying these complex methods to real cancer clinical trials. Thus, the book aims to furnish researchers in biostatistics and statistical science with a good summary of recent developments of adaptive dose-finding methods as well as providing practitioners in biostatistics and clinical investigators with advanced materials for designing, conducting, monitoring, and analyzing adaptive dose-finding trials. The topics in the book are mainly related to cancer clinical trials, but many of those topics are potentially applicable or can be extended to trials for other diseases. The focus is mainly on model-based dose-finding methods for two kinds of phase I trials. One is clinical trials with combinations of two agents. Development of dose-finding methods for two-agent combination trials requires reasonable models that can adequately capture joint toxicity probabilities for two agents, taking into consideration possible interactions of the two agents on toxicity probability such as synergistic or antagonistic effects. Another is clinical trials for evaluating both efficacy and toxicity outcomes in single- and two-agent combination trials. These methods are often applied to the phase I trials including MTAs because the toxicity and efficacy for a MTA does not monotonically increase with dose, but the efficacy often increases initially with the dose and then plateaus. Successful software implementations for several dose-finding methods are introduced in the book, and their operating characteristics in practice are discussed. Recent advance of the adaptive dose-finding methods in drug developments are also provided.
This book provides a comprehensive introduction to statistical methods for designing early phase dose-finding clinical trials. It will serve as a textbook or handbook for graduate students and practitioners in biostatistics and clinical investigators who are involved in designing, conducting, monitoring, and analyzing dose-finding trials. The book will also provide an overview of advanced topics and discussions in this field for the benefit of researchers in biostatistics and statistical science. Beginning with backgrounds and fundamental notions on dose finding in early phase clinical trials, the book then provides traditional and recent dose-finding designs of phase I trials for, e.g., cytotoxic agents in oncology, to evaluate toxicity outcome. Included are rule-based and model-based designs, such as 3 + 3 designs, accelerated titration designs, toxicity probability interval designs, continual reassessment method and related designs, and escalation overdose control designs. This book also covers more complex and updated dose-finding designs of phase I-II and I/II trials for cytotoxic agents, and cytostatic agents, focusing on both toxicity and efficacy outcomes, such as designs with covariates and drug combinations, maximum tolerated dose-schedule finding designs, and so on.
MRS of the Brain and Neurological Disorders illustrates and demonstrates the usefulness of magnetic resonance spectroscopy for the diagnosis of brain and neurological disorders, including epilepsy, nervous disorders, psychiatric disorders, and brain tumors. The book is unique in that it contains 87 case studies of neurologic and psychiatric diso
In the context of an aging society and the challenges posed by the COVID-19 pandemic, ensuring a healthy life expectancy has become a pressing social concern. Amidst the pandemic's impact on medical systems worldwide, the need for advancements in early diagnosis, minimally invasive treatments, and infectious disease countermeasures has been reaffirmed. The demand for practical solutions, including new drugs, medical devices, and healthcare systems, is vocalized by healthcare professionals. To address these challenges, engineering researchers play a crucial role in swiftly translating their technological innovations into medical applications. In this book, cutting-edge researchers introduce biomedical engineering from materials, devices, imaging, and information. The chapter contributors are major members of the Research Center for Biomedical Engineering, Japan. This text discusses topics on biomaterials (Chapters 1 to 3), medical devices (Chapters 4 to 11), basic medicine and dentistry (Chapters 12 to 15), and medical systems (Chapters 16 and 17). All of the topics are important areas in biomedical engineering.
Following the Great East Japan Earthquake on March 11, 2011, tsunamis engulfed the Fukushima Daiichi nuclear power plant located on Japan's Pacific Coast, leading to the worst nuclear disaster the world has seen since the Chernobyl crisis of 1986. Prior to this disaster, Japan had the third largest commercial nuclear program in the world, surpassed only by those in the United States and France—nuclear power significantly contributed to Japan's economic prosperity, and nearly 30% of Japan's electricity was generated by reactors dotted across the archipelago, from northern Hokkaido to southern Kyushu. This long period of institutional stasis was, however, punctuated by the crisis of March 11, which became a critical juncture for Japanese nuclear policymaking. As Akihiro Ogawa argues, the primary agent for this change is what he calls "antinuclear citizens"— a conscientious Japanese public who envision a sustainable life in a nuclear-free society. Drawing on over a decade of ethnographic research conducted across Japan—including antinuclear rallies, meetings with bureaucrats, and at renewable energy production sites—Ogawa presents an historical record of ordinary people's actions as they sought to survive and navigate a new reality post-Fukushima. Ultimately, Ogawa argues that effective sustainability efforts require collaborations that are grounded in civil society and challenge hegemonic ideology, efforts that reimagine societies and landscapes—especially those dominated by industrial capitalism—to help build a productive symbiosis between industry and sustainability.
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