LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Wolowacz, S.; Pearson, I.; Shannon, P.; Chubb, B.; Gundgaard, J.; Davies, M.; Briggs, A. (2015)
Publisher: John Wiley & Sons Ltd.
Languages: English
Types: Article
Subjects:
Identifiers:doi:10.1111/dme.12663
Aims:\ud To develop a health economic model to evaluate the cost-effectiveness of new interventions for Type 1 diabetes mellitus by their effects on long-term complications (measured through mean HbA1c) while capturing the impact of treatment on hypoglycaemic events.\ud \ud Methods:\ud Through a systematic review, we identified complications associated with Type 1 diabetes mellitus and data describing the long-term incidence of these complications. An individual patient simulation model was developed and included the following complications: cardiovascular disease, peripheral neuropathy, microalbuminuria, end-stage renal disease, proliferative retinopathy, ketoacidosis, cataract, hypoglycemia and adverse birth outcomes. Risk equations were developed from published cumulative incidence data and hazard ratios for the effect of HbA1c, age and duration of diabetes. We validated the model by comparing model predictions with observed outcomes from studies used to build the model (internal validation) and from other published data (external validation). We performed illustrative analyses for typical patient cohorts and a hypothetical intervention.\ud \ud Results:\ud Model predictions were within 2% of expected values in the internal validation and within 8% of observed values in the external validation (percentages represent absolute differences in the cumulative incidence).\ud \ud Conclusions:\ud The model utilized high-quality, recent data specific to people with Type 1 diabetes mellitus. In the model validation, results deviated less than 8% from expected values.

Share - Bookmark

Cite this article