title: An alternative approach to modelling HbA1c trajectories in patients with type 2 diabetes mellitus.
abstract: Time-dependent HbA1c trajectories in health economic models of type 2 diabetes mellitus (T2DM) are typically informed by the UK Prospective Diabetes Study (UKPDS). However, this approach may not accurately predict HbA1c progression in patients who do not conform to the demographic profile of the original UKPDS cohort. This study aimed to develop an alternative mathematical model (MM) to simulate HbA1c progression in T2DM.
  
  
  
  A systematic literature review identified studies, published between 2005 and 2015, that reported HbA1c in adult T2DM patients over a minimum duration of 18 months. Pooled data from eligible studies were used to develop an alternative MM equation for HbA1c progression, which was then contrasted with the UKPDS 68 progression equation in illustrative scenarios.
  
  
  
  A total of 68 studies were eligible for data extraction (mean follow-up time 4.1 years). HbA1c progression was highly heterogeneous across studies, varying with baseline HbA1c, treatment group and patient age. The MM equation was fitted with parameters for mean baseline HbA1c (8.3%), initial change in HbA1c (-0.62%) and upper quartile of maximum observed HbA1c (9.3%). Differences in HbA1c trajectories between the MM and UKPDS approaches altered the timing of therapy escalation in illustrative scenarios.
  
  
  
  The MM represents an alternative approach to simulate HbA1c trajectories in T2DM models, as UKPDS data may not adequately reflect the heterogeneity of HbA1c profiles observed in clinical studies. However, the choice of approach should ultimately be determined by the characteristics of individual patients under consideration and the clinical face validity of the modelled trajectories.
authors.affiliation: Health Economics and Outcomes Research Ltd, Cardiff, UK.|Swansea Centre for Health Economics, Swansea University, Swansea, UK.
authors.forename: Phil
authors.initials: P
authors.lastname: McEwan
authors.affiliation: Health Economics and Outcomes Research Ltd, Cardiff, UK.
authors.forename: Hayley
authors.initials: H
authors.lastname: Bennett
authors.affiliation: Global Health Economics and Payer Analytics, AstraZeneca, Gaithersburg, Maryland.
authors.forename: Lei
authors.initials: L
authors.lastname: Qin
authors.affiliation: Global Health Economics and Payer Analytics, AstraZeneca, Gothenburg, Sweden.
authors.forename: Klas
authors.initials: K
authors.lastname: Bergenheim
authors.affiliation: Health Economics and Outcomes Research Ltd, Cardiff, UK.|School of Medicine, University of Nottingham, Nottingham, UK.
authors.forename: Jason
authors.initials: J
authors.lastname: Gordon
authors.affiliation: University Hospital Llandough, Cardiff, UK.
authors.forename: Marc
authors.initials: M
authors.lastname: Evans
mesh_terms: D003131:Combined Modality Therapy / Q000009:adverse effects; D003198:Computer Simulation; D003924:Diabetes Mellitus, Type 2 / Q000097:blood* / Q000178:diet therapy / Q000188:drug therapy / Q000503:physiopathology; D003927:Diet, Diabetic; D018450:Disease Progression; D016903:Drug Monitoring; D004359:Drug Therapy, Combination / Q000009:adverse effects; D004470:Economics, Medical; D019317:Evidence-Based Medicine; D005260:Female; D006442:Glycated Hemoglobin / Q000032:analysis*; D006801:Humans; D006943:Hyperglycemia / Q000517:prevention & control*; D007003:Hypoglycemia / Q000139:chemically induced / Q000517:prevention & control*; D007004:Hypoglycemic Agents / Q000009:adverse effects / Q000627:therapeutic use; D007333:Insulin Resistance; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D010353:Patient Education as Topic
chemical_list: D006442:Glycated Hemoglobin; D007004:Hypoglycemic Agents; C517652:hemoglobin A1c protein, human
keywords: glycaemic control; pharmaco-economics; systematic review; type 2 diabetes