A shiny app for modeling the lifetime in primary breast cancer patients through phase-type distributions

TL;DR

This paper introduces an accessible shiny app that allows users to model and compare phase-type distributions for primary breast cancer patient survival data without programming knowledge.

Contribution

The paper presents a user-friendly web application for fitting and assessing phase-type distributions to survival data, filling a gap in statistical software tools.

Findings

The app enables easy comparison of multiple PHD fits.

It accurately estimates parameters and assesses goodness of fit.

Demonstrated with breast cancer patient survival data.

Abstract

Phase-type distributions (PHDs), which are defined as the distribution of the lifetime up to the absorption in an absorbent Markov chain, are an appropriate candidate to model the lifetime of any system, since any non-negative probability distribution can be approximated by a PHD with sufficient precision. Despite PHD potential, friendly statistical programs do not have a module implemented in their interfaces to handle PHD. Thus, researchers must consider others statistical software such as R, Matlab or Python that work with the compilation of code chunks and functions. This fact might be an important handicap for those researchers who do not have sufficient knowledge in programming environments. In this paper, a new interactive web application developed with shiny is introduced in order to adjust PHD to an experimental dataset. This open access app does not require any kind of knowledge about programming or major mathematical concepts. Users can easily compare the graphic fit of several PHDs while estimating their parameters and assess the goodness of fit with just several clicks. All these functionalities are exhibited by means of a numerical simulation and modeling the time to live since the diagnostic in primary breast cancer patients.