Inhaltsangabe
Network meta-analyses and mixed treatment comparisons represent the uppermost level in the evidence hierarchy for decision making, in medicine as well as in other scholarly fields. They combine and exploit data from direct (i.e. head-to-head) randomised trials and combine them, when appropriate, with indirect estimates, in order to obtain more precise and robust estimates of effect to determine which management strategy is the safest, most effective, or cost-effective. They have been developed recently thanks to the current widespread availability of high power computers, but have already succeeded in becoming a highly read and impactful type of research design. Several important examples of network meta-analyses with pivotal practical implications are available, spanning from stents for coronary revascularisation to psychiatric drugs. This book, the first devoted solely to this topic, aims to cover briefly but poignantly the main topics which should be mastered to critically read and interpret as well as, if deemed worthwhile, perform and report independently a network meta-analysis and mixed treatment comparison. The editorial team represents a veritable Who's Who of world-wide experts in these topics, and everyone involved in the collection has strived to provide correct and sound yet practical advice. This book includes dozens of tables and illustrations to guide visually the reader in understanding the basics as well as the more refined details of network meta-analyses. Quoted references are per se a uniquely useful component of this book, as they provide a commented guidance to the best and most informative papers on mixed treatment comparisons. Thus, this book will be uniquely useful to students or scholars interested in these topics, including clinical researchers and practitioners, as well as statisticians, epidemiologists, psychologists and sociologists.
Reseña del editor
Network meta-analyses and mixed treatment comparisons represent the uppermost level in the evidence hierarchy for decision making, in medicine as well as in other scholarly fields. They combine and exploit data from direct (i.e. head-to-head) randomised trials and combine them, when appropriate, with indirect estimates, in order to obtain more precise and robust estimates of effect to determine which management strategy is the safest, most effective, or cost-effective. They have been developed recently thanks to the current widespread availability of high power computers, but have already succeeded in becoming a highly read and impactful type of research design. Several important examples of network meta-analyses with pivotal practical implications are available, spanning from stents for coronary revascularisation to psychiatric drugs. This book, the first devoted solely to this topic, aims to cover briefly but poignantly the main topics which should be mastered to critically read and interpret as well as, if deemed worthwhile, perform and report independently a network meta-analysis and mixed treatment comparison. The editorial team represents a veritable Who's Who of world-wide experts in these topics, and everyone involved in the collection has strived to provide correct and sound yet practical advice. This book includes dozens of tables and illustrations to guide visually the reader in understanding the basics as well as the more refined details of network meta-analyses. Quoted references are per se a uniquely useful component of this book, as they provide a commented guidance to the best and most informative papers on mixed treatment comparisons. Thus, this book will be uniquely useful to students or scholars interested in these topics, including clinical researchers and practitioners, as well as statisticians, epidemiologists, psychologists and sociologists.
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