A comparative study of prevalence‐based incidence estimation techniques with application to dementia data in Germany

Abstract

Dementia is becoming a major health burden, which is mainly due to the increasing life expectancy in many developed countries. To describe the disease progression of individuals, multistate models are generally appropriate tools. These models allow the individuals to move along a path consisting of a finite number of disease states. We consider a simplifying illness-death model in which the subjects progress through the states healthy, diseased and dead. We use this model to study analytic relationships between the prevalence, incidence and mortality rates of irreversible diseases that have been applied in the past. One of these approaches is a rather recently proposed technique based on an ordinary differential equation (ODE). We conduct a simulation study to compare the performance of two suggested numerical approximations of this ODE with three alternative techniques, the common goal of which is to estimate age-specific incidence from cross-sectional information. The quality of the estimation methods is further explored using data on dementia in Germany. In the simulation scenarios as well as in the dementia data setting, the ODE method turns out to be the predominant technique with regard to the quality of the estimation of the known incidence regimes.

Age-specific and sex-specific incidence of systemic lupus erythematosus: an estimate from cross-sectional claims data of 2.3 million people in the German statutory health insurance 2002

“…The estimation of the age-specific incidence is accomplished indirectly via a mathematical method, which has demonstrated higher accuracy compared with all hitherto existing methods of incidence estimation from prevalence data 14. By the epidemiological rule that the prevalence equals the product of the mean incidence and the mean duration, it can be shown that our estimated incidence rate is consistent with the prevalence data (see the online supplementary file for details).…”

Illness-Death Model in Chronic Disease Epidemiology: Characteristics of a Related, Differential Equation and an Inverse Problem

“…Hence, the consequences in practical epidemiology are presumably small. In addition, it has recently been shown that, for the task of estimating incidence rates from prevalence data, methods based on ODEs, like the one presented in this article, are superior compared to other methods [ 21 ].…”

Estimation of chronic kidney disease incidence from prevalence and mortality data in American Indians with type 2 diabetes

“…The applicability of the illness-death model for extracting incidence density estimates from prevalence and mortality data has been demonstrated previously for chronic diseases such as renal replacement therapy [ 24 ], dementia [ 25 ], and diabetes [ 26 ]. The present study adds to previous information by replicating the model in a non-Caucasian population and accounting for the remission rate of a chronic disease.…”