scholarly journals ASSESSING THE IMPACT OF SIMULATED TIME HORIZON ON PREDICTED INCREMENTAL QUALITY ADJUSTED LIFE YEARS IN TYPE 2 DIABETES

2016 ◽  
Vol 19 (3) ◽  
pp. A87
Author(s):  
V. Foos ◽  
M. Lamotte ◽  
P. McEwan
2019 ◽  
Vol 39 (3) ◽  
pp. 239-252 ◽  
Author(s):  
Sung Eun Choi ◽  
Seth A. Berkowitz ◽  
John S. Yudkin ◽  
Huseyin Naci ◽  
Sanjay Basu

Background. Personalizing medical treatment often requires practitioners to compare multiple treatment options, assess a patient’s unique risk and benefit from each option, and elicit a patient’s preferences around treatment. We integrated these 3 considerations into a decision-modeling framework for the selection of second-line glycemic therapy for type 2 diabetes. Methods. Based on multicriteria decision analysis, we developed a unified treatment decision support tool accounting for 3 factors: patient preferences, disease outcomes, and medication efficacy and safety profiles. By standardizing and multiplying these 3 factors, we calculated the ranking score for each medication. This approach was applied to determining second-line glycemic therapy by integrating 1) treatment efficacy and side-effect data from a network meta-analysis of 301 randomized trials ( N = 219,277), 2) validated risk equations for type 2 diabetes complications, and 3) patient preferences around treatment (e.g., to avoid daily glucose testing). Data from participants with type 2 diabetes in the U.S. National Health and Nutrition Examination Survey (NHANES 2003–2014, N = 1107) were used to explore variations in treatment recommendations and associated quality-adjusted life-years given different patient features. Results. Patients at the highest microvascular disease risk had glucagon-like peptide 1 agonists or basal insulin recommended as top choices, whereas those wanting to avoid an injected medication or daily glucose testing had sodium-glucose linked transporter 2 or dipeptidyl peptidase 4 inhibitors commonly recommended, and those with major cost concerns had sulfonylureas commonly recommended. By converting from the most common sulfonylurea treatment to the model-recommended treatment, NHANES participants were expected to save an average of 0.036 quality-adjusted life-years per person (about a half month) from 10 years of treatment. Conclusions. Models can help integrate meta-analytic treatment effect estimates with individualized risk calculations and preferences, to aid personalized treatment selection.


Author(s):  
Junxiu Liu ◽  
Dariush Mozaffarian ◽  
Stephen Sy ◽  
Yujin Lee ◽  
Parke E. Wilde ◽  
...  

Background: Excess caloric intake is linked to weight gain, obesity, and related diseases, including type 2 diabetes mellitus and cardiovascular disease (CVD). Obesity incidence is rising, with nearly 3 in 4 US adults being overweight or obese. In 2018, the US federal government finalized the implementation of mandatory labeling of calorie content on all menu items across major chain restaurants nationally as a strategy to support informed consumer choice, reduce caloric intake, and potentially encourage restaurant reformulations. Yet, the potential health and economic impacts of this policy remain unclear. Methods and Results: We used a validated microsimulation model (CVD-PREDICT) to estimate reductions in CVD events, diabetes mellitus cases, gains in quality-adjusted life years, costs, and cost-effectiveness of the menu calorie labeling intervention, based on consumer responses alone, and further accounting for potential industry reformulation. The model incorporated nationally representative demographic and dietary data from National Health and Nutrition Examination Surveys 2009 to 2016; policy effects on consumer diets and body mass index-disease effects from published meta-analyses; and policy effects on industry reformulation, policy costs (policy administration, industry compliance, and reformulation), and health-related costs (formal and informal healthcare costs, productivity costs) from established sources or reasonable assumptions. We modeled change in calories to change in weight using an established dynamic weight-change model, assuming 50% of expected calorie reductions would translate to long-term reductions. Findings were evaluated over 5 years and a lifetime from healthcare and societal perspectives, with uncertainty incorporated in both 1-way and probabilistic sensitivity analyses. Between 2018 and 2023, implementation of the restaurant menu calorie labeling law was estimated, based on consumer response alone, to prevent 14 698 new CVD cases (including 1575 CVD deaths) and 21 522 new type 2 diabetes mellitus cases, gaining 8749 quality-adjusted life years. Over a lifetime, corresponding values were 135 781 new CVD cases (including 27 646 CVD deaths), 99 736 type 2 diabetes mellitus cases, and 367 450 quality-adjusted life years. Assuming modest restaurant item reformulation, both health and economic benefits were estimated to be about 2-fold larger than based on consumer response alone. The consumer response alone was estimated to be cost-saving by 2023, with net lifetime savings of $10.42B from a healthcare perspective and $12.71B from a societal perspective. Findings were robust in a range of sensitivity analyses. Conclusions: Our national model suggests that the full implementation of the US calorie menu labeling law will generate significant health gains and healthcare and societal cost-savings. Industry responses to modestly reformulate menu items would provide even larger additional benefits.


2020 ◽  
Author(s):  
Jose Leal ◽  
Shelby D Reed ◽  
Rishi Patel ◽  
Oliver Rivero-Arias ◽  
Yanhong Li ◽  
...  

<b>Objective</b>: To estimate using the United Kingdom Prospective Diabetes Study Outcomes Model Version 2 (UKPDS-OM2) the impact of delaying type 2 diabetes onset on costs and quality-adjusted life expectancy using trial participants who developed diabetes in the NAVIGATOR study. <p><b>Research design and methods</b>: We simulated the impact of delaying diabetes onset by one to nine years, utilising data from the 3058 of 9306 NAVIGATOR trial participants who developed type 2 diabetes. Costs and utility weights associated with diabetes and diabetes-related complications were obtained for US and UK settings, with costs expressed in 2017 values. We estimated discounted lifetime costs and quality-adjusted life years (QALYs) with 95% confidence intervals.</p> <p><b>Results</b>: Gains in QALYs increased from 0.02 (95% CI: 0.01, 0.03; US setting) to 0.15 (95% CI: 0.11, 0.20; US setting) as the imposed time to diabetes onset was increased from one to nine years, respectively. Savings in complication costs increased from $1,388 (95%CI: $1,092, $1,669) for one-year delay to $8,437 (95% CI: $5603, $8630) for a delay of nine years. Interventions costing up to $567-$2,680 and £201-£947 per year would be cost-effective at $100,000 per QALY and £20,000 per QALY thresholds in the US and UK, respectively, as the modelled delay in diabetes onset was increased from one to nine years. </p> <p><b>Conclusions</b>: Simulating a hypothetical diabetes-delaying intervention provides guidance concerning the maximum cost and minimum delay in diabetes onset needed to be cost-effective. These results can inform the ongoing debate about diabetes prevention strategies and the design of future intervention studies. </p>


2020 ◽  
Author(s):  
Jose Leal ◽  
Shelby D Reed ◽  
Rishi Patel ◽  
Oliver Rivero-Arias ◽  
Yanhong Li ◽  
...  

<b>Objective</b>: To estimate using the United Kingdom Prospective Diabetes Study Outcomes Model Version 2 (UKPDS-OM2) the impact of delaying type 2 diabetes onset on costs and quality-adjusted life expectancy using trial participants who developed diabetes in the NAVIGATOR study. <p><b>Research design and methods</b>: We simulated the impact of delaying diabetes onset by one to nine years, utilising data from the 3058 of 9306 NAVIGATOR trial participants who developed type 2 diabetes. Costs and utility weights associated with diabetes and diabetes-related complications were obtained for US and UK settings, with costs expressed in 2017 values. We estimated discounted lifetime costs and quality-adjusted life years (QALYs) with 95% confidence intervals.</p> <p><b>Results</b>: Gains in QALYs increased from 0.02 (95% CI: 0.01, 0.03; US setting) to 0.15 (95% CI: 0.11, 0.20; US setting) as the imposed time to diabetes onset was increased from one to nine years, respectively. Savings in complication costs increased from $1,388 (95%CI: $1,092, $1,669) for one-year delay to $8,437 (95% CI: $5603, $8630) for a delay of nine years. Interventions costing up to $567-$2,680 and £201-£947 per year would be cost-effective at $100,000 per QALY and £20,000 per QALY thresholds in the US and UK, respectively, as the modelled delay in diabetes onset was increased from one to nine years. </p> <p><b>Conclusions</b>: Simulating a hypothetical diabetes-delaying intervention provides guidance concerning the maximum cost and minimum delay in diabetes onset needed to be cost-effective. These results can inform the ongoing debate about diabetes prevention strategies and the design of future intervention studies. </p>


2009 ◽  
Vol 12 (7) ◽  
pp. A415
Author(s):  
MW Jo ◽  
WJ Lee ◽  
JH Non ◽  
Y Choi ◽  
KH Song

2020 ◽  
Author(s):  
Chi Heem Wong ◽  
Dexin Li ◽  
Nina Wang ◽  
Jonathan Gruber ◽  
Rena Conti ◽  
...  

AbstractWe assess the potential financial impact of future gene therapies by identifying the 109 late-stage gene therapy clinical trials currently underway, estimating the prevalence and incidence of their corresponding diseases, developing novel mathematical models of the increase in quality-adjusted life years for each approved gene therapy, and simulating the launch prices and the expected spending of these therapies over a 15-year time horizon. The results of our simulation suggest that an expected total of 1.09 million patients will be treated by gene therapy from January 2020 to December 2034. The expected peak annual spending on these therapies is $25.3 billion, and the total spending from January 2020 to December 2034 is $306 billion. We decompose their annual estimated spending by treated age group as a proxy for U.S. insurance type, and consider the tradeoffs of various methods of payment for these therapies to ensure patient access to their expected benefits.


2011 ◽  
Vol 2011 ◽  
pp. 1-14 ◽  
Author(s):  
Jeroen P. Jansen ◽  
Stephanie D. Taylor

Objectives. To evaluate the cost-effectiveness of etoricoxib (90 mg) relative to celecoxib (200/400 mg), and the nonselective NSAIDs naproxen (1000 mg) and diclofenac (150 mg) in the initial treatment of ankylosing spondylitis in Norway.Methods. A previously developed Markov state-transition model was used to estimate costs and benefits associated with initiating treatment with the different competing NSAIDs. Efficacy, gastrointestinal and cardiovascular safety, and resource use data were obtained from the literature. Data from different studies were synthesized and translated into direct costs and quality adjusted life years by means of a Bayesian comprehensive decision modeling approach.Results. Over a 30-year time horizon, etoricoxib is associated with about 0.4 more quality adjusted life years than the other interventions. At 1 year, naproxen is the most cost-saving strategy. However, etoricoxib is cost and quality adjusted life year saving relative to celecoxib, as well as diclofenac and naproxen after 5 years of follow-up. For a willingness-to-pay ceiling ratio of 200,000 Norwegian krones per quality adjusted life year, there is a >95% probability that etoricoxib is the most-cost-effective treatment when a time horizon of 5 or more years is considered.Conclusions. Etoricoxib is the most cost-effective NSAID for initiating treatment of ankylosing spondylitis in Norway.


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