Multimorbidity as a multistage disease process

Abstract

There is a growing proportion of people with several disease conditions ("multimorbidity"), placing increasing demands on healthcare systems. One hypothesis is that clusters of diseases may arise from shared underlying disease processes (shared "pathogenesis"), whereby the presence of one disease indicates the state of disease progression to several related disease types. This article explains how this hypothesis can be tested using observational data for disease incidence. Specifically, a multistage model is used to test whether two diseases can have a "shared stage" or "step", before either disease can occur, and how the unobserved rate of this step can be determined. The approach offers a simple method for studying multiple diseases and identifying shared underlying causes of multiple conditions, and is illustrated with published data and numerical examples. The fundamental mathematical model is analysed to compare key statistical properties such as the expectation and variance with those of independent diseases. The main results do not need an understanding of the underlying mathematics and can be appreciated by a non-expert. Significance: It is widely believed that there are shared underlying pathways that can lead to several disease types (shared "pathogenesis"), and this may explain observed clusters of disease types. This article shows how this hypothesis can be tested for a pair or cluster of diseases, using observational data of disease incidence.