![]() Furthermore, QOL data are available only in the UKPDS1. The UKPDS followed more than 4,000 patients for the longest period, making it possible to simulate end-stage events, such as second myocardial infarction and stroke. For moreĭetails, see supplementary materials in Hayes et at.1Īmong the models in Table 1, the UKPDS outcomes model 2, the JJ risk engine3 and the risk equations from the Swedish National Diabetes Register4 were developed by using individual patient data, but the others were constructed by synthesizing summary statistics reported in the literature, such as incidence rate and mean QOL value5,6. The simulated lifetime is weighted by utility values to account for its quality, yielding an estimate of QALY. A utility value, which is usually estimated by quality-of-life (QOL) questionnaires, reflects the quality of a patient's lifetime with the corresponding diabetic complication. Third, in the case of death, the calculation is terminated otherwise, information on risk factors and event history is updated at t = 1, and the same calculation is repeated annually until death. ![]() Mortality depends on the first step that is, it will be higher if a transition to a diabetic complication occurs at t = 0. Second, mortality is calculated at t = 0 by using a risk equation. First, at time-point t = 0, risk factors and event history of patients are input into risk equations, yielding the probabilities of transition. Simulation by the UKPDS outcomes model 2 is carried out as the following steps on an annual cycle. The probabilities of each transition depend on the risk factors shown in Table 1, and the relationships between the probabilities and the risk factors are expressed as risk equations1,3-6. The incidence of a diabetic complication is viewed as a transition from a 'no-complication' state to the disease state. A health economic model for diabetes generally consists of three elements: disease states and transitions risk equations and utility values of each disease state ranging from 0 to 1. ![]() Table 1 summarizes previously developed health economic models for diabetes. In that analysis, the QALY of diabetes patients was estimated by computer simulation using the UKPDS outcomes model. Hirohito Sone Tel.: +81-2 Fax: +81-2 E-mailaddress: Received 16 January 2014 accepted 20 January 2014 Sitag-liptin is, for example, recommended by NICE Short Clinical Guideline 87 as an additional agent instead of a sulfonyl-urea in second-line therapy because of its incremental cost-effectiveness ratio of £1,567 per one quality-adjusted life year (QALY) as compared with rosiglitazone2.Ĭorresponding author. In the UK, the standard of care recommended by the health technology assessment body - the National Institute for Health and Clinical Excellence (NICE) - are determined on the basis of the results of clinical trials and cost-effectiveness analysis. Such models can be useful in two different situations: first, medical decision-making for example, recommendation of statin therapy based on absolute cardiovascular risk and second, health technology assessment based on efficacy and cost-effectiveness. Given the longevity of patients with diabetes, there is no doubt that accurate simulation of lifetime outcomes requires data with a minimum follow-up period of more than 10 years.Ĭonsiderable efforts have been devoted to developing models for simulating outcomes of patients with diabetes. Official Journal of the Asian Association for the Study of DiabetesĬommentary on the United Kingdom Prospective Diabetes Study outcomes model Need for long-term follow up and quality of life data in Asian patientsĪ paper by Hayes et at.1 published in Diabetologia in June 2013 reports an updated version of the United Kingdom Prospective Diabetes Study (UKPDS) outcomes model developed on the basis of data from 5,102 patients from the original UKPDS and 4,031 survivors enrolled in the 10-year post-trial study. Journal of Diabetes Investigation Open access
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