title: Validation of the IHE Cohort Model of Type 2 Diabetes and the impact of choice of macrovascular risk equations.
abstract: BACKGROUND
  Health-economic models of diabetes are complex since the disease is chronic, progressive and there are many diabetic complications. External validation of these models helps building trust and satisfies demands from decision makers. We evaluated the external validity of the IHE Cohort Model of Type 2 Diabetes; the impact of using alternative macrovascular risk equations; and compared the results to those from microsimulation models.
  
  
  METHODS
  The external validity of the model was analysed from 12 clinical trials and observational studies by comparing 167 predicted microvascular, macrovascular and mortality outcomes to the observed study outcomes. Concordance was examined using visual inspection of scatterplots and regression-based analysis, where an intercept of 0 and a slope of 1 indicate perfect concordance. Additional subgroup analyses were conducted on 'dependent' vs. 'independent' endpoints and microvascular vs. macrovascular vs. mortality endpoints.
  
  
  RESULTS
  Visual inspection indicates that the model predicts outcomes well. The UKPDS-OM1 equations showed almost perfect concordance with observed values (slope 0.996), whereas Swedish NDR (0.952) and UKPDS-OM2 (0.899) had a slight tendency to underestimate. The R2 values were uniformly high (>0.96). There were no major differences between 'dependent' and 'independent' outcomes, nor for microvascular and mortality outcomes. Macrovascular outcomes tended to be underestimated, most so for UKPDS-OM2 and least so for NDR risk equations.
  
  
  CONCLUSIONS
  External validation indicates that the IHE Cohort Model of Type 2 Diabetes has predictive accuracy in line with microsimulation models, indicating that the trade-off in accuracy using cohort simulation might not be that large. While the choice of risk equations was seen to matter, each were associated with generally reasonable results, indicating that the choice must reflect the specifics of the application. The largest variation was observed for macrovascular outcomes. There, NDR performed best for relatively recent and well-treated patients, while UKPDS-OM1 performed best for the older UKPDS cohort.
authors.affiliation: The Swedish Institute for Health Economics, IHE, Lund, Sweden.
authors.forename: Adam
authors.initials: A
authors.lastname: Lundqvist
authors.affiliation: The Swedish Institute for Health Economics, IHE, Lund, Sweden; Department of Clinical Sciences, Lund University, Malmö, Sweden.
authors.forename: Katarina
authors.initials: K
authors.lastname: Steen Carlsson
authors.affiliation: The Swedish Institute for Health Economics, IHE, Lund, Sweden.
authors.forename: Pierre
authors.initials: P
authors.lastname: Johansen
authors.affiliation: The Swedish Institute for Health Economics, IHE, Lund, Sweden.
authors.forename: Emelie
authors.initials: E
authors.lastname: Andersson
authors.affiliation: The Swedish Institute for Health Economics, IHE, Lund, Sweden.
authors.forename: Michael
authors.initials: M
authors.lastname: Willis
mesh_terms: D002318:Cardiovascular Diseases / Q000453:epidemiology* / Q000209:etiology*; D048909:Diabetes Complications / Q000453:epidemiology*; D003924:Diabetes Mellitus, Type 2 / Q000150:complications*; D006801:Humans; D015994:Incidence; D008962:Models, Theoretical; D063868:Patient Outcome Assessment; D015203:Reproducibility of Results; D012306:Risk