A novel decision model to predict the impact of weight management interventions: The Core Obesity Model

Aims: Models are needed to quantify the economic implications of obesity in relation to health outcomes and health-related quality of life. This report presents the structure of the Core Obesity Model (COM) and compare its predictions with the UK clinical practice data.

Materials and methods: The COM is a Markov, closed-cohort model, which expands on earlier obesity models by including prediabetes as a risk factor for type 2 diabetes (T2D), and sleep apnea and cancer as health outcomes. Selected outcomes predicted by the COM were compared with observed event rates from the Clinical Practice Research Datalink-Hospital Episode Statistics (CPRD-HES) study. The importance of baseline prediabetes prevalence, a factor not taken into account in previous economic models of obesity, was tested in a scenario analysis using data from the 2011 Health Survey of England.

Results: Cardiovascular (CV) event rates predicted by the COM were well matched with those in the CPRD-HES study (7.8-8.5 per 1000 patient-years across BMI groups) in both base case and scenario analyses (8.0-9.4 and 8.6-9.9, respectively). Rates of T2D were underpredicted in the base case (1.0-7.6 vs. 2.1-22.7) but increased to match those observed in CPRD-HES for some BMI groups when a prospectively collected prediabetes prevalence was used (2.7-13.1). Mortality rates in the CPRD-HES were consistently higher than the COM predictions, especially in higher BMI groups.

Conclusions: The COM predicts the occurrence of CV events and T2D with a good degree of accuracy, particularly when prediabetes is included in the model, indicating the importance of considering this risk factor in economic models of obesity.