title: Influence of comorbidities on therapeutic progression of diabetes treatment in Australian veterans: a cohort study.
abstract: BACKGROUND
  This study assessed whether the number of comorbid conditions unrelated to diabetes was associated with a delay in therapeutic progression of diabetes treatment in Australian veterans.
  
  
  RESULTS
  A retrospective cohort study was undertaken using data from the Australian Department of Veterans' Affairs (DVA) claims database between July 2000 and June 2008. The study included new users of metformin or sulfonylurea medicines. The outcome was the time to addition or switch to another antidiabetic treatment. The total number of comorbid conditions unrelated to diabetes was identified using the pharmaceutical-based comorbidity index, Rx-Risk-V. Competing risk regression analyses were conducted, with adjustments for a number of covariates that included age, gender, residential status, use of endocrinology service, number of hospitalisation episodes and adherence to diabetes medicines. Overall, 20,134 veterans were included in the study. At one year, 23.5% of patients with diabetes had a second medicine added or had switched to another medicine, with 41.4% progressing by 4 years. The number of unrelated comorbidities was significantly associated with the time to addition of an antidiabetic medicine or switch to insulin (subhazard ratio [SHR] 0.87 [95% CI 0.84-0.91], P<0.001). Depression, cancer, chronic obstructive pulmonary disease, dementia, and Parkinson's disease were individually associated with a decreased likelihood of therapeutic progression. Age, residential status, number of hospitalisations and adherence to anti-diabetic medicines delayed therapeutic progression.
  
  
  CONCLUSIONS
  Increasing numbers of unrelated conditions decreased the likelihood of therapeutic progression in veterans with diabetes. These results have implications for the development of quality measures, clinical guidelines and the construction of models of care for management of diabetes in elderly people with comorbidities.
authors.affiliation: Quality Use of Medicines and Pharmacy Research Centre, Sansom Institute for Health Research, University of South Australia, Adelaide, South Australia, Australia. agnes.vitry@unisa.edu.au
authors.forename: Agnes I
authors.initials: AI
authors.lastname: Vitry
authors.forename: Elizabeth E
authors.initials: EE
authors.lastname: Roughead
authors.forename: Adrian K
authors.initials: AK
authors.lastname: Preiss
authors.forename: Philip
authors.initials: P
authors.lastname: Ryan
authors.forename: Emmae N
authors.initials: EN
authors.lastname: Ramsay
authors.forename: Andrew L
authors.initials: AL
authors.lastname: Gilbert
authors.forename: Gillian E
authors.initials: GE
authors.lastname: Caughey
authors.forename: Sepehr
authors.initials: S
authors.lastname: Shakib
authors.forename: Adrian
authors.initials: A
authors.lastname: Esterman
authors.forename: Ying
authors.initials: Y
authors.lastname: Zhang
authors.forename: Robyn A
authors.initials: RA
authors.lastname: McDermott
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001315:Australia / Q000453:epidemiology; D015331:Cohort Studies; D015897:Comorbidity; D016208:Databases, Factual / Q000706:statistics & numerical data; D003924:Diabetes Mellitus, Type 2 / Q000188:drug therapy* / Q000453:epidemiology* / Q000473:pathology; D018450:Disease Progression; D005260:Female; D006801:Humans; D007004:Hypoglycemic Agents / Q000627:therapeutic use*; D015994:Incidence; D008297:Male; D012044:Regression Analysis; D016896:Treatment Outcome; D014728:Veterans / Q000706:statistics & numerical data*
chemical_list: D007004:Hypoglycemic Agents