Abstract
BackgroundMulti-state models are used in complex disease pathways to describe a process where an individual moves from one state to the next, taking into account competing states during each transition. In a multi-state setting, there are various measures to be estimated that are of great epidemiological importance. However, increased complexity of the multi-state setting and predictions over time for individuals with different covariate patterns may lead to increased difficulty in communicating the estimated measures. The need for easy and meaningful communication of the analysis results motivated the development of a web tool to address these issues.ResultsMSMplus is a publicly available web tool, developed via the Shiny R package, with the aim of enhancing the understanding of multi-state model analyses results. The results from any multi-state model analysis are uploaded to the application in a pre-specified format. Through a variety of user-tailored interactive graphs, the application contributes to an improvement in communication, reporting and interpretation of multi-state analysis results as well as comparison between different approaches. The predicted measures that can be supported by MSMplus include, among others, the transition probabilities, the transition intensity rates, the length of stay in each state, the probability of ever visiting a state and user defined measures. Representation of differences, ratios and confidence intervals of the aforementioned measures are also supported. MSMplus is a useful tool that enhances communication and understanding of multi-state model analyses results.ConclusionsFurther use and development of web tools should be encouraged in the future as a means to communicate scientific research.
Highlights
Multi-state models are used in complex disease pathways to describe a process where an individual moves from one state to the taking into account competing states during each transition
The European Blood and Marrow Transplant registry (EBMT) example consists of 2204 patients who received bone marrow transplantation
MSMplus is a web tool designed for communicating multi-state analysis results in a flexible and meaningful way
Summary
Multi-state models are used in complex disease pathways to describe a process where an individual moves from one state to the taking into account competing states during each transition. Increased complexity of the multi-state setting and predictions over time for individuals with different covariate patterns may lead to increased difficulty in communicating the estimated measures. Studying acute [1] or chronic disease progression [2], recurrent events such as repeated hospitalizations [3] are typical examples of multi-state models use. If the measures of interest are functions of time (e.g non time constant transition intensity rates and probabilities), graphical displays of these measures may be more suitable when studying dynamic, time-dependent processes
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