ArticlesAge at initiation and frequency of screening to detect type 2 diabetes: a cost-effectiveness analysis
Introduction
The worldwide incidence, prevalence, and economic effect of type 2 diabetes are substantial. Since the disease is usually asymptomatic in its earliest stages, many cases remain undiagnosed for long periods.1 Upon diagnosis, many individuals already have diabetes-related complications.2 Several organisations have recommended screening algorithms to identify individuals with undiagnosed type 2 diabetes to help reduce the burden of the disease.3, 4, 5
Since no clinical trials have compared the benefits of starting screening at various ages and with different intervals to detect new cases of type 2 diabetes, most recommendations for screening have been based on mathematical models.6, 7, 8, 9, 10, 11, 12, 13 Our review of these analyses shows that the models used have not been extensively validated to determine their accuracy, do not address repetitive screening with defined intervals, compare a very limited number of screening algorithms, and do not compare the effects of screening asymptomatic individuals with screening symptomatic individuals.
To address these issues, we have calculated the cost-effectiveness of a range of simulated screening strategies to detect new cases of type 2 diabetes compared with testing simulated people only after symptoms develop.
Section snippets
Mathematical model
For this cost-effectiveness analysis, we used the Archimedes model, a detailed, person-by-person, large-scale simulation model of physiology, disease, and health-care systems. This model uses many ordinary and differential equations to represent normal physiology, and a wide range of diseases and disorders related to diabetes and its complications, tests, treatments, care processes, health outcomes, visits and hospital admissions, procedures, and related costs.
All conditions pertinent to an
Results
Figure 1 shows the cumulative proportion of simulated people diagnosed with type 2 diabetes over 50 years of follow-up for each screening strategy. With each age that screening started, there was a rapid rise in the cumulative proportion of simulated people with type 2 diabetes that gradually approximated the incidence obtained with maximum screening. The cumulative proportion of simulated people diagnosed with type 2 diabetes was much lower for the strategies in which screening started upon
Discussion
Our study shows that a range of simulated screening strategies could reduce the rate of myocardial infarction, microvascular events, and deaths in people with type 2 diabetes compared with no screening. For example, if screening is started at 30 years of age and repeated every 3 years, about seven myocardial infarctions per 1000 people aged 30 years could be prevented over 50 years. The same screening strategy can be expected to add about 171 QALYs per 1000 people.
The small beneficial effect of
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