title: Cardiovascular risk prediction models for people with severe mental illness: results from the prediction and management of cardiovascular risk in people with severe mental illnesses (PRIMROSE) research program.
abstract: OBJECTIVE
  People with severe mental illness (SMI), including schizophrenia and bipolar disorder, have excess rates of cardiovascular disease (CVD). Risk prediction models validated for the general population may not accurately estimate cardiovascular risk in this group.
  
  
  OBJECTIVE
  To develop and validate a risk model exclusive to predicting CVD events in people with SMI incorporating established cardiovascular risk factors and additional variables.
  
  
  METHODS
  We used anonymous/deidentified data collected between January 1, 1995, and December 31, 2010, from the Health Improvement Network (THIN) to conduct a primary care, prospective cohort and risk score development study in the United Kingdom. Participants included 38,824 people with a diagnosis of SMI (schizophrenia, bipolar disorder, or other nonorganic psychosis) aged 30 to 90 years. During a median follow-up of 5.6 years, 2324 CVD events (6.0%) occurred.
  
  
  METHODS
  Ten-year risk of the first cardiovascular event (myocardial infarction, angina pectoris, cerebrovascular accidents, or major coronary surgery). Predictors included age, sex, height, weight, systolic blood pressure, diabetes mellitus, smoking, body mass index (BMI), lipid profile, social deprivation, SMI diagnosis, prescriptions for antidepressants and antipsychotics, and reports of heavy alcohol use.
  
  
  RESULTS
  We developed 2 CVD risk prediction models for people with SMI: the PRIMROSE BMI model and the PRIMROSE lipid model. These models mutually excluded lipids and BMI. In terms of discrimination, from cross-validations for men, the PRIMROSE lipid model D statistic was 1.92 (95% CI, 1.80-2.03) and C statistic was 0.80 (95% CI, 0.76-0.83) compared with 1.74 (95% CI, 1.63-1.86) and 0.78 (95% CI, 0.75-0.82) for published Cox Framingham risk scores. The corresponding results in women were 1.87 (95% CI, 1.76-1.98) and 0.79 (95% CI, 0.76-0.82) for the PRIMROSE lipid model and 1.58 (95% CI, 1.48-1.68) and 0.77 (95% CI, 0.73-0.81) for the Cox Framingham model. Discrimination statistics for the PRIMROSE BMI model were comparable to those for the PRIMROSE lipid model. Calibration plots suggested that both PRIMROSE models were superior to the Cox Framingham models.
  
  
  CONCLUSIONS
  The PRIMROSE BMI and lipid CVD risk prediction models performed better in SMI compared with models that include only established CVD risk factors. Further work on the clinical effectiveness and cost-effectiveness of the PRIMROSE models is needed to ascertain the best thresholds for offering CVD interventions.
authors.affiliation: Division of Psychiatry, UCL (University College London), London, United Kingdom2Camden and Islington National Health Service Foundation Trust, London, United Kingdom.
authors.forename: David P J
authors.initials: DP
authors.lastname: Osborn
authors.affiliation: Division of Psychiatry, UCL (University College London), London, United Kingdom3Research Department of Primary Care and Population Health, UCL, London, United Kingdom.
authors.forename: Sarah
authors.initials: S
authors.lastname: Hardoon
authors.affiliation: Department of Statistical Science, UCL, London, United Kingdom.
authors.forename: Rumana Z
authors.initials: RZ
authors.lastname: Omar
authors.affiliation: Human Development and Health Academic Unit, Faculty of Medicine, University of Southampton, Southampton, United Kingdom.
authors.forename: Richard I G
authors.initials: RI
authors.lastname: Holt
authors.affiliation: Division of Psychiatry, UCL (University College London), London, United Kingdom2Camden and Islington National Health Service Foundation Trust, London, United Kingdom.
authors.forename: Michael
authors.initials: M
authors.lastname: King
authors.affiliation: Rethink Mental Illness, London, United Kingdom.
authors.forename: John
authors.initials: J
authors.lastname: Larsen
authors.affiliation: Research Department of Primary Care and Population Health, UCL, London, United Kingdom.
authors.forename: Louise
authors.initials: L
authors.lastname: Marston
authors.affiliation: Research Department of Primary Care and Population Health, UCL, London, United Kingdom.
authors.forename: Richard W
authors.initials: RW
authors.lastname: Morris
authors.affiliation: Research Department of Primary Care and Population Health, UCL, London, United Kingdom.
authors.forename: Irwin
authors.initials: I
authors.lastname: Nazareth
authors.affiliation: Research Department of Primary Care and Population Health, UCL, London, United Kingdom.
authors.forename: Kate
authors.initials: K
authors.lastname: Walters
authors.affiliation: Research Department of Primary Care and Population Health, UCL, London, United Kingdom.
authors.forename: Irene
authors.initials: I
authors.lastname: Petersen
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001714:Bipolar Disorder / Q000453:epidemiology*; D002318:Cardiovascular Diseases / Q000175:diagnosis / Q000453:epidemiology*; D015897:Comorbidity; D057286:Electronic Health Records / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011379:Prognosis; D011618:Psychotic Disorders / Q000453:epidemiology*; D012306:Risk; D012559:Schizophrenia / Q000453:epidemiology*; D006113:United Kingdom / Q000453:epidemiology