1. Volume 20, Issue 7, Pages 985-991 (July 2017)
The Prime Diabetes Model: Novel Methods for Estimating Long-Term Clinical and Cost Outcomes in Type 1 Diabetes Mellitus 
William J. Valentine, PhD, Richard F. Pollock, MA, Rhodri Saunders, PhD, Jay Bae, PhD, Kirsi Norrbacka, MSc, Kristina Boye, PhD, MPH 
Value in Health 
Volume 20, Issue 7, Pages (July 2017)
DOI: /j.jval
Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Terms and Conditions

2. Fig. 1
Schematic diagram of the PRIME Diabetes Model. Interactions between complication controllers are indicated by red arrows. X, risk of mortality is associated with this complication controller; ▲, SBP is a direct risk factor; •, HbA1c is a direct risk factor; ■, BMI is a direct risk factor. BMI, body mass index; HbA1c, glycated hemoglobin; SBP, systolic blood pressure.
Value in Health  , DOI: ( /j.jval )
Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Terms and Conditions

3. Fig. 2
Modeled and actual cumulative incidence of first CVD events in multiple patient populations: (A) SNDR; (B) EuroDiab; (C) FinnDiane Registry; (D) WESDR; (E) DCCT (myocardial infarction and stroke only); and (F) DCCT. Each graph shows the cumulative incidence of first events (myocardial infarction, angina, and stroke [with the exception of subpart (E), in which only myocardial infarction and stroke are shown]) on the y-axis, plotted against time in years on the x-axis. CVD, cardiovascular disease; DCCT, Diabetes Control and Complications Trial; SNDR, Swedish National Diabetes Register; WESDR, Wisconsin Epidemiologic Study of Diabetic Retinopathy.
Value in Health  , DOI: ( /j.jval )
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4. Fig. 3
Comparison of nephropathy outcomes between DCCT data and the PRIME Diabetes Model. PRIME Diabetes Model results are presented as an area graph by year in the background. Data taken from de Boer et al. [11] are overlaid as a stacked bar graph with data in 2-y blocks. Micro, microalbuminuria; normal, normal renal status; overt, overt nephropathy.
Value in Health  , DOI: ( /j.jval )
Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Terms and Conditions

5. Fig. 4
Performance of the PRIME Diabetes Model in predicting retinopathy outcomes (PDR or worse) in the DCCT intensive treatment cohort. External validation of the PRIME Diabetes Model (blue line) vs. the DCCT intensive treatment arm (black dots) of the cumulative incidence of PDR or worse. DCCT, Diabetes Control and Complications Trial; PDR, proliferative diabetic retinopathy.
Value in Health  , DOI: ( /j.jval )
Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Terms and Conditions

6. Fig. 5
Performance of the PRIME Diabetes Model in predicting amputation outcomes in the SNDR. Internal validation of the model vs. SNDR data for lower extremity amputation. Cumulative probabilities from the model were indexed by patient age to generate outcomes analogous to the published registry data. Model outcomes are shown in blue (male) and red (female), and broken (male) and solid (female) gray lines indicate the registry data. CEA, cost-effectiveness analysis; SNDR, Swedish National Diabetes Register.
Value in Health  , DOI: ( /j.jval )
Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Terms and Conditions