Estimating the cost-effectiveness of lifestyle intervention programmes to prevent diabetes based on an example from Germany: Markov modelling

Abstract

BackgroundType 2 diabetes mellitus (T2D) poses a large worldwide burden for health care systems. One possible tool to decrease this burden is primary prevention. As it is unethical to wait until perfect data are available to conclude whether T2D primary prevention intervention programmes are cost-effective, we need a model that simulates the effect of prevention initiatives. Thus, the aim of this study is to investigate the long-term cost-effectiveness of lifestyle intervention programmes for the prevention of T2D using a Markov model. As decision makers often face difficulties in applying health economic results, we visualise our results with health economic tools.MethodsWe use four-state Markov modelling with a probabilistic cohort analysis to calculate the cost per quality-adjusted life year (QALY) gained. A one-year cycle length and a lifetime time horizon are applied. Best available evidence supplies the model with data on transition probabilities between glycaemic states, mortality risks, utility weights, and disease costs. The costs are calculated from a societal perspective. A 3% discount rate is used for costs and QALYs. Cost-effectiveness acceptability curves are presented to assist decision makers.ResultsThe model indicates that diabetes prevention interventions have the potential to be cost-effective, but the outcome reveals a high level of uncertainty. Incremental cost-effectiveness ratios (ICERs) were negative for the intervention, ie, the intervention leads to a cost reduction for men and women aged 30 or 50 years at initiation of the intervention. For men and women aged 70 at initiation of the intervention, the ICER was EUR27,546/QALY gained and EUR19,433/QALY gained, respectively. In all cases, the QALYs gained were low. Cost-effectiveness acceptability curves show that the higher the willingness-to-pay threshold value, the higher the probability that the intervention is cost-effective. Nonetheless, all curves are flat. The threshold value of EUR50,000/QALY gained has a 30-55% probability that the intervention is cost-effective.ConclusionsLifestyle interventions for primary prevention of type 2 diabetes are cost-saving for men and women aged 30 or 50 years at the start of the intervention, and cost-effective for men and women aged 70 years. However, there is a high degree of uncertainty around the ICERs. With the conservative approach adopted for this model, the long-term effectiveness of the intervention could be underestimated.

The Effect of Deterministic and Stochastic Approaches on Cost-Utility Results Under Uncertainty: A Markov Chain Monte Carlo Simulation Application on Diabetes

“…tarafından diyabet hastalığı ile ilgili tanımlanmış dört farklı durum ve markov geçiş olasılıkları ile maliyet ve fayda (utility) değerleri kullanılarak simülasyon uygulaması yapılmıştır. 11 …”

“…tarafından diyabet konusunda yapılan çalışmada kullanılan durumlar arası geçiş olasılıkları, maliyet ve değerler kullanılmıştır. 11 Yaşam tarzı ile ilgili müdahalelerin MD bakımından incelendiği bu modelde, döngü süresi bir yıl olarak belirlenmiştir. Çalışmada modelin başlangıcında bireylerin %16'sı BGT iken, %84'ü NGT ve sıfır kişi T2D'dir.…”

“…In this study it is aimed to compare model performances in terms of uncertainty by using deterministic and stochastic approaches. Metarial and Methods: Secondary data was used in the study and markov model and transition probabilities conssists of four states determined by Neumann et al (2011) about the role of life intervention programs to prevent diabetes examined. Deterministic and stochastic model results were simulated by using Markov Chain Monte Carlo Simulation and incremental cost utility ratio (ICUR) was determined.…”

Type 2 Diabetes Prevention Programs; How Far are we?

“…Short time-horizon studies have shown prediabetes lifestyle interventions to be cost-effective and even cost saving. Long time-horizon studies based on 10 to 30 year predictive mathematical models have used different models with different data, and have come to different conclusions about the cost-effectiveness of prediabetes lifestyle interventions [54][55][56][68][69][70][71][72][73][74][75][76][77]. Predictive models are useful, but they also have limitations.…”

“…The cost-effectiveness of lifestyle interventions has been examined in a number of clinical trials and computer modelling simulations. Although pharmacological interventions have also been shown to prevent diabetes, the cost effectiveness and risk-benefit ratio are less clear [32][33][34][53][54][55][56][57][58][59][60][61][62][63].…”