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

Estimation of mortality rate ratios for chronic conditions with misclassification of disease status at death

Estimation of mortality rates and mortality rate ratios (MRR) of diseased and non-diseased individuals is a core metric of disease impact used in chronic disease epidemiology. Estimation of mortality rates is often conducted through retrospective linkage of information from nationwide surveys such as the National Health Interview Survey (NHIS) and death registries. These surveys usually collect information on disease status during only one study visit. This infrequency leads to missing disease information (with right censored survival times) for deceased individuals who were disease-free at study participation, and a possibly biased estimation of the MRR because of possible undetected disease onset after study participation. This occurrence is called "misclassification of disease status at death (MicDaD)" and it is a potentially common source of bias in epidemiologic studies. In this study, we conducted a simulation analysis with a high and a low incidence setting to assess the extent of MicDaD-bias in the estimated mortality. For the simulated populations, MRR for diseased and non-diseased individuals with and without MicDaD were calculated and compared. Magnitude of MicDaD-bias depends on and is driven by the incidence of the chronic disease under consideration; our analysis revealed a noticeable shift towards underestimation for high incidences when MicDaD is present. Impact of MicDaD was smaller for lower incidence (but associated with greater uncertainty in the estimation of MRR in general). Further research can consider the amount of missing information and potential influencers such as duration and risk factors of the disease.

Future prevalence of type 2 diabetes—A comparative analysis of chronic disease projection methods

Background

Accurate projections of the future number of people with chronic diseases are necessary for effective resource allocation and health care planning in response to changes in disease burden.

Aim

To introduce and compare different projection methods to estimate the number of people with diagnosed type 2 diabetes (T2D) in Germany in 2040.

Methods

We compare three methods to project the number of males with T2D in Germany in 2040. Method 1) simply combines the sex- and age-specific prevalence of T2D in 2010 with future population distributions projected by the German Federal Statistical Office (FSO). Methods 2) and 3) additionally account for the incidence of T2D and mortality rates using partial differential equations (PDEs). Method 2) models the prevalence of T2D employing a scalar PDE which incorporates incidence and mortality rates. Subsequently, the estimated prevalence is applied to the population projection of the FSO. Method 3) uses a two-dimensional system of PDEs and estimates future case numbers directly while future mortality of people with and without T2D is modelled independently from the projection of the FSO.

Results

Method 1) projects 3.6 million male people with diagnosed T2D in Germany in 2040. Compared to 2.8 million males in 2010, this equals an increase by 29%. Methods 2) and 3) project 5.9 million (+104% compared to 2010) and 6.0 million (+116%) male T2D patients, respectively.

Conclusions

The results of the three methods differ substantially. It appears that ignoring temporal trends in incidence and mortality may result in misleading projections of the future number of people with chronic diseases. Hence, it is essential to include these rates as is done by method 2) and 3).

Incidence and prevalence of inflammatory bowel disease in Devon, UK

BACKGROUND AND AIMS

We sought to define temporal changes in prevalence of inflammatory bowel disease (IBD) in East Devon, UK, in order to facilitate service planning over the next 5 years.

METHODS

Multiple primary and secondary care databases were used to identify and verify cases. Point prevalence and incidence of IBD were reported in April 2017 and from 2008 to 2016, respectively. Future prevalence and healthcare activity requirements were estimated by linear regression.

RESULTS

Prevalence of ulcerative colitis (UC), Crohn's disease (CD) and inflammatory bowel disease unclassified (IBDU) were 479.72, 265.94 and 35.34 per 100 000 persons, respectively. In 2016, the incidence rates of UC, CD and IBDU were 15.4, 10.7 and 1.4 per 100 000 persons per year, respectively. There were no significant changes in the incidence of CD (p=0.49, R=0.26) or UC (p=0.80, R=0.10). IBD prevalence has increased by 39.9% (95% CI 28.2 to 53.7) in the last 10 years without differences in the rate of change between UC and CD. Overall, 27% of patients were managed in primary care, a quarter of whom were eligible but not receiving endoscopic surveillance. Outpatient clinics, MRI and biologic use, but not helpline calls, admissions, or surgeries increased over and above the change in IBD prevalence.

CONCLUSIONS

We report one of the highest prevalence and incidence rates of IBD from Northern Europe. Overall, IBD incidence is static, but prevalence is increasing. We estimate that 1% of our population will live with IBD between 2025 and 2030.

New ways of estimating excess mortality of chronic diseases from aggregated data: insights from the illness-death model

Background

Recently, we have shown that the age-specific prevalence of a disease can be related to the transition rates in the illness-death model via a partial differential equation (PDE). The transition rates are the incidence rate, the remission rate and mortality rates from the ‘Healthy’ and ‘Ill’ states. In case of a chronic disease, we now demonstrate that the PDE can be used to estimate the excess mortality from age-specific prevalence and incidence data. For the prevalence and incidence, aggregated data are sufficient - no individual subject data are needed, which allows application of the methods in contexts of strong data protection or where data from individual subjects is not accessible.

Methods

After developing novel estimators for the excess mortality derived from the PDE, we apply them to simulated data and compare the findings with the input values of the simulation aiming to evaluate the new approach. In a practical application to claims data from 35 million men insured by the German public health insurance funds, we estimate the population-wide excess mortality of men with diagnosed type 2 diabetes.

Results

In the simulation study, we find that the estimation of the excess mortality is feasible from prevalence and incidence data if the prevalence is given at two points in time. The accuracy of the method decreases as the temporal difference between these two points in time increases. In our setting, the relative error was 5% and below if the temporal difference was three years or less. Application of the new method to the claims data yields plausible findings for the excess mortality of type 2 diabetes in German men.

Conclusions

The described approach is useful to estimate the excess mortality of a chronic condition from aggregated age-specific incidence and prevalence data.

Trial registration

The article does not report the results of any health care intervention.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-7201-7) contains supplementary material, which is available to authorized users.