Citations 3
An Overview and Recent Developments in the Analysis of Multistate Processes
Gorfine, Malka , Andersen, Per Kragh , Therneau, Terry M. , Joly, Pierre , Abrahamowicz, Michał , Initiative, Topic Group 8 “Survival Analysis” of the STRATOS, Pohar Perme, Maja , Abrahamowicz, Michal , Kragh Andersen, Per , Cook, Richard J. , Putter, Hein , Initiative, Topic Group 8 “Survival Analysis” of the STRATOS
Statistics in Medicine | May 14, 2026 | Volume: 45 | Issue: 10-12 | Pages: No page available
ABSTRACT Multistate models offer a powerful framework for studying disease processes and can be used to formulate intensity‐based and more descriptive marginal regression models. They also represent a natural foundation for the construction of joint models for disease processes and dynamic marker processes, as well as joint models incorporating random censoring and intermittent observation times. This article reviews the ways multistate models can be formed and fitted to life history data. Recent work on pseudo‐values and the incorporation of random effects to model dependence on the process history and between‐process heterogeneity are also discussed. The software available to facilitate such analyses is listed.
Assessing Performance and Clinical Usefulness in Prediction Models With Survival Outcomes: Practical Guidance for Cox Proportional Hazards Models
McLernon, David J. , Giardiello, Daniele , Calster, Ben Van , Wynants, Laure , Geloven, Nan van , Smeden, Maarten van , Therneau, Terry M. , Steyerberg, Ewout W. , Initiative, topic groups 6 and 8 of the STRATOS, Collins, Professor Gary S. , Karr, Kathleen, Moons, Carl, Westphal, Max , Joly, Pierre Benoît, Taylor, Jeremy M. G. , Van Calster, Ben , van Geloven, Nan , van Smeden, Maarten , Therneau, Terry , Collins, Gary , Initiative, topic groups 6 and 8 of the STRATOS, Bossuyt, Patrick M. , Boyles, Tom Hilary , Macaskill, Petra , Vickers, Andrew J , Abrahamowicz, Michał , Gorfine, Malka , Ambrogi, Federico , Cook, Richard, Joly, Pierre, Andersen, Per Kragh , Martinussen, Torben , Pohar Perme, Maja , Putter, Hein
Annals of Internal Medicine | December 26, 2022 | Volume: 176 | Issue: 1 | Pages: 105-114
Analysis of time‐to‐event for observational studies: Guidance to the use of intensity models
Andersen, Per Kragh , Houwelingen, Hans C. van , Cook, Richard J. , Joly, Pierre , Taylor, Jeremy M. G. , Abrahamowicz, Michał , Therneau, Terry M. , Kragh Andersen, Per , Pohar Perme, Maja , Cook, Richard J , Abrahamowicz, Michal , Martinussen, Torben
Statistics in Medicine | October 11, 2020 | Volume: 40 | Issue: 1 | Pages: 185-211
Summary This paper provides guidance for researchers with some mathematical background on the conduct of time‐to‐event analysis in observational studies based on intensity (hazard) models. Discussions of basic concepts like time axis, event definition and censoring are given. Hazard models are introduced, with special emphasis on the Cox proportional hazards regression model. We provide check lists that may be useful both when fitting the model and assessing its goodness of fit and when interpreting the results. Special attention is paid to how to avoid problems with immortal time bias by introducing time‐dependent covariates. We discuss prediction based on hazard models and difficulties when attempting to draw proper causal conclusions from such models. Finally, we present a series of examples where the methods and check lists are exemplified. Computational details and implementation using the freely available R software are documented in Supplementary Material. The paper was prepared as part of the STRATOS initiative.