Competing Risks and Multistate Models with R
Competing Risks and Multistate Models with R covers models that generalize the analysis of time to a single event (survival analysis) to analyzing the timing of distinct terminal events (competing risks) and possible intermediate events (multistate models
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Jan Beyersmann • Arthur Allignol Martin Schumacher
Competing Risks and Multistate Models with R
Jan Beyersmann Institute of Medical Biometry and Medical Informatics University Medical Center Freiburg Freiburg Center for Data Analysis and Modelling University of Freiburg D-79104 Freiburg, Germany
Arthur Allignol Institute of Medical Biometry and Medical Informatics University Medical Center Freiburg Freiburg Center for Data Analysis and Modelling University of Freiburg D-79104 Freiburg, Germany
Martin Schumacher Institute of Medical Biometry and Medical Informatics University Medical Center Freiburg D-79104 Freiburg, Germany
ISBN 978-1-4614-2034-7 e-ISBN 978-1-4614-2035-4 DOI 10.1007/978-1-4614-2035-4 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2011941794 ¤ Springer Science+Business Media, LLC 2012 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
This book is about applied statistical analysis of competing risks and multistate data. Competing risks generalize standard survival analysis of a single, often composite or combined endpoint to investigating multiple first event types. A standard example from clinical oncology is progression-free survival, which is the time until death or disease progression, whatever occurs first. A usual survival analysis studies the length of progression-free survival only. A competing risks analysis would disentangle the composite endpoint by investigating the time of progression-free survival and the event type, either progression or death without prior progression. Competing risks are the simplest multistate model, where events are envisaged as transitions between states. For competing risks, there is one common initial state and as many target states as there are competing event types. Only transitions between the initial state and the competing risks states are considered. A multistate model that is more complex than competing risks is the illness-death model. In the example of progression-free survival, this multistate model would also investigate death after progression. In principle, a multistate model consists of any finite number of states, and any transition between any pair of states can be considered.
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