Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/41284
Title: Parametric multistate survival models: Flexible modelling allowing transition-specific distributions with application to estimating clinically useful measures of effect differences
Authors: Crowther, Michael J.
Lambert, Paul C
First Published: 5-Sep-2017
Publisher: Wiley
Citation: Statistics in Medicine, 2017, 36 (29), pp. 4719-4742
Abstract: Multistate models are increasingly being used to model complex disease profiles. By modelling transitions between disease states, accounting for competing events at each transition, we can gain a much richer understanding of patient trajectories and how risk factors impact over the entire disease pathway. In this article, we concentrate on parametric multistate models, both Markov and semi-Markov, and develop a flexible framework where each transition can be specified by a variety of parametric models including exponential, Weibull, Gompertz, Royston-Parmar proportional hazards models or log-logistic, log-normal, generalised gamma accelerated failure time models, possibly sharing parameters across transitions. We also extend the framework to allow time-dependent effects. We then use an efficient and generalisable simulation method to calculate transition probabilities from any fitted multistate model, and show how it facilitates the simple calculation of clinically useful measures, such as expected length of stay in each state, and differences and ratios of proportion within each state as a function of time, for specific covariate patterns. We illustrate our methods using a dataset of patients with primary breast cancer. User-friendly Stata software is provided.
DOI Link: 10.1002/sim.7448
ISSN: 0277-6715
eISSN: 1097-0258
Links: http://hdl.handle.net/2381/41284
http://onlinelibrary.wiley.com/doi/10.1002/sim.7448/full
Version: Post-print
Status: Peer-reviewed
Type: Journal Article
Rights: Copyright © 2017, Wiley. Deposited with reference to the publisher’s open access archiving policy.
Description: The file associated with this record is under embargo until 12 months after publication, in accordance with the publisher's self-archiving policy. The full text may be available through the publisher links provided above.
Appears in Collections:Published Articles, Dept. of Health Sciences

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