Literature DB >> 33517494

Targeting of the diabetes prevention program leads to substantial benefits when capacity is constrained.

Natalia Olchanski1, David van Klaveren2, Joshua T Cohen2, John B Wong2,3, Robin Ruthazer2, David M Kent2.   

Abstract

OBJECTIVE: Approximately 84 million people in the USA have pre-diabetes, but only a fraction of them receive proven effective therapies to prevent type 2 diabetes. We estimated the value of prioritizing individuals at highest risk of progression to diabetes for treatment, compared to non-targeted treatment of individuals meeting inclusion criteria for the Diabetes Prevention Program (DPP).
METHODS: Using microsimulation to project outcomes in the DPP trial population, we compared two interventions to usual care: (1) lifestyle modification and (2) metformin administration. For each intervention, we compared targeted and non-targeted strategies, assuming either limited or unlimited program capacity. We modeled the individualized risk of developing diabetes and projected diabetic outcomes to yield lifetime costs and quality-adjusted life expectancy, from which we estimated net monetary benefits (NMB) for both lifestyle and metformin versus usual care.
RESULTS: Compared to usual care, lifestyle modification conferred positive benefits and reduced lifetime costs for all eligible individuals. Metformin's NMB was negative for the lowest population risk quintile. By avoiding use when costs outweighed benefits, targeted administration of metformin conferred a benefit of $500 per person. If only 20% of the population could receive treatment, when prioritizing individuals based on diabetes risk, rather than treating a 20% random sample, the difference in NMB ranged from $14,000 to $20,000 per person.
CONCLUSIONS: Targeting active diabetes prevention to patients at highest risk could improve health outcomes and reduce costs compared to providing the same intervention to a similar number of patients with pre-diabetes without targeted selection.

Entities:  

Keywords:  Diabetes prevention; Economic analysis; Heterogeneity of treatment effect; Lifestyle modification; Risk based; Type 2 diabetes; Value

Mesh:

Substances:

Year:  2021        PMID: 33517494      PMCID: PMC8276501          DOI: 10.1007/s00592-021-01672-3

Source DB:  PubMed          Journal:  Acta Diabetol        ISSN: 0940-5429            Impact factor:   4.280


  30 in total

1.  Cost-effectiveness of 10-Year Risk Thresholds for Initiation of Statin Therapy for Primary Prevention of Cardiovascular Disease.

Authors:  Ankur Pandya; Stephen Sy; Sylvia Cho; Milton C Weinstein; Thomas A Gaziano
Journal:  JAMA       Date:  2015-07-14       Impact factor: 56.272

2.  Net health benefits: a new framework for the analysis of uncertainty in cost-effectiveness analysis.

Authors:  A A Stinnett; J Mullahy
Journal:  Med Decis Making       Date:  1998 Apr-Jun       Impact factor: 2.583

3.  The cost-effectiveness of lifestyle modification or metformin in preventing type 2 diabetes in adults with impaired glucose tolerance.

Authors:  William H Herman; Thomas J Hoerger; Michael Brandle; Katherine Hicks; Stephen Sorensen; Ping Zhang; Richard F Hamman; Ronald T Ackermann; Michael M Engelgau; Robert E Ratner
Journal:  Ann Intern Med       Date:  2005-03-01       Impact factor: 25.391

4.  Cost and clinical implications of diabetes prevention in an Australian setting: a long-term modeling analysis.

Authors:  A J Palmer; D M D Tucker
Journal:  Prim Care Diabetes       Date:  2011-12-06       Impact factor: 2.459

5.  10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study.

Authors:  William C Knowler; Sarah E Fowler; Richard F Hamman; Costas A Christophi; Heather J Hoffman; Anne T Brenneman; Janet O Brown-Friday; Ronald Goldberg; Elizabeth Venditti; David M Nathan
Journal:  Lancet       Date:  2009-10-29       Impact factor: 79.321

6.  Effect of patients' risks and preferences on health gains with plasma glucose level lowering in type 2 diabetes mellitus.

Authors:  Sandeep Vijan; Jeremy B Sussman; John S Yudkin; Rodney A Hayward
Journal:  JAMA Intern Med       Date:  2014-08       Impact factor: 21.873

7.  Impact of Lifestyle and Metformin Interventions on the Risk of Progression to Diabetes and Regression to Normal Glucose Regulation in Overweight or Obese People With Impaired Glucose Regulation.

Authors:  William H Herman; Qing Pan; Sharon L Edelstein; Kieren J Mather; Leigh Perreault; Elizabeth Barrett-Connor; Dana M Dabelea; Edward Horton; Steven E Kahn; William C Knowler; Carlos Lorenzo; Xavier Pi-Sunyer; Elizabeth Venditti; Wen Ye
Journal:  Diabetes Care       Date:  2017-10-11       Impact factor: 19.112

8.  The impact of Type 2 diabetes prevention programmes based on risk-identification and lifestyle intervention intensity strategies: a cost-effectiveness analysis.

Authors:  P R Breeze; C Thomas; H Squires; A Brennan; C Greaves; P J Diggle; E Brunner; A Tabak; L Preston; J Chilcott
Journal:  Diabet Med       Date:  2017-03-10       Impact factor: 4.359

9.  Lessons from Launching the Diabetes Prevention Program in a Large Integrated Health Care Delivery System: A Case Study.

Authors:  Colin D Rehm; Melinda E Marquez; Elizabeth Spurrell-Huss; Nicole Hollingsworth; Amanda S Parsons
Journal:  Popul Health Manag       Date:  2017-01-11       Impact factor: 2.459

10.  Selecting the optimal risk threshold of diabetes risk scores to identify high-risk individuals for diabetes prevention: a cost-effectiveness analysis.

Authors:  Kristin Mühlenbruch; Xiaohui Zhuo; Barbara Bardenheier; Hui Shao; Michael Laxy; Andrea Icks; Ping Zhang; Edward W Gregg; Matthias B Schulze
Journal:  Acta Diabetol       Date:  2019-11-19       Impact factor: 4.280

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