Cost-effectiveness of detemir-based basal/bolus therapy versus NPH-based basal/bolus therapy for type 1 diabetes in a UK setting: an economic analysis based on meta-analysis results of four clinical trials

Abstract

Short-term improvements seen with IDet combinations versus NPH combinations led to decreased complications, improvements in QALYs and reductions in complication costs, which partially offset the additional costs of detemir, leading to a cost-effectiveness ratio which fell within a range considered to represent excellent value for money (< 35,000 pounds sterling/QALY gained).

Validation of the IMS CORE Diabetes Model

“…The CDM has been used extensively to evaluate the cost-effectiveness of new therapies for the treatment of diabetes [4][5][6][7][8]. The model is also routinely used to inform reimbursement decisions, public health issues, resource planning, clinical trial design, and optimal patient management strategies [9][10][11][12].…”

Optimal strategies for identifying kidney disease in diabetes: properties of screening tests, progression of renal dysfunction and impact of treatment – systematic review and modelling of progression and cost-effectiveness

“…Patient-level simulation models are common in type 2 diabetes; there are Markov models of the progression of type 1 diabetes, [158][159][160] and more general simulation models have been used for economic evaluation. 161 Most of the existing simulation models for use in type 1 diabetes have been developed using information from other patient populations to capture transitions between important health states. For example, the risk of CVD has been estimated from the Framingham study, 162 or using equations developed with data obtained from type 2 diabetes patients in the UKPDS.…”

A Cost-Effectiveness Analysis to Illustrate the Impact of Cost Definitions on Results, Interpretations and Comparability of Pharmacoeconomic Studies in the US

“…The IMS-CDM has been previously described in detail and validated, [13,14] and has been used in a number of studies to model the cost effectiveness of interventions and management tools for both type 1 and type 2 diabetes. [15][16][17] Each of the sub-models has a Markov structure. Monte Carlo simulation and tracker variables account for multiple complications at the patient level.…”