title: The performance of seven QPrediction risk scores in an independent external sample of patients from general practice: a validation study.
abstract: OBJECTIVE
  To validate the performance of a set of risk prediction algorithms developed using the QResearch database, in an independent sample from general practices contributing to the Clinical Research Data Link (CPRD).
  
  
  METHODS
  Prospective open cohort study using practices contributing to the CPRD database and practices contributing to the QResearch database.
  
  
  METHODS
  The CPRD validation cohort consisted of 3.3 million patients, aged 25-99 years registered at 357 general practices between 1 Jan 1998 and 31 July 2012. The validation statistics for QResearch were obtained from the original published papers which used a one-third sample of practices separate to those used to derive the score. A cohort from QResearch was used to compare incidence rates and baseline characteristics and consisted of 6.8 million patients from 753 practices registered between 1 Jan 1998 and until 31 July 2013.
  
  
  METHODS
  Incident events relating to seven different risk prediction scores: QRISK2 (cardiovascular disease); QStroke (ischaemic stroke); QDiabetes (type 2 diabetes); QFracture (osteoporotic fracture and hip fracture); QKidney (moderate and severe kidney failure); QThrombosis (venous thromboembolism); QBleed (intracranial bleed and upper gastrointestinal haemorrhage). Measures of discrimination and calibration were calculated.
  
  
  RESULTS
  Overall, the baseline characteristics of the CPRD and QResearch cohorts were similar though QResearch had higher recording levels for ethnicity and family history. The validation statistics for each of the risk prediction scores were very similar in the CPRD cohort compared with the published results from QResearch validation cohorts. For example, in women, the QDiabetes algorithm explained 50% of the variation within CPRD compared with 51% on QResearch and the receiver operator curve value was 0.85 on both databases. The scores were well calibrated in CPRD.
  
  
  CONCLUSIONS
  Each of the algorithms performed practically as well in the external independent CPRD validation cohorts as they had in the original published QResearch validation cohorts.
authors.affiliation: Division of Primary Care, Nottingham, UK.
authors.forename: Julia
authors.initials: J
authors.lastname: Hippisley-Cox
authors.affiliation: Division of Primary Care, Nottingham, UK.
authors.forename: Carol
authors.initials: C
authors.lastname: Coupland
authors.affiliation: Avon Primary Care Research Collaborative, Bristol Clinical Commissioning Group, Bristol, UK.
authors.forename: Peter
authors.initials: P
authors.lastname: Brindle
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D002138:Calibration; D002318:Cardiovascular Diseases / Q000209:etiology; D003920:Diabetes Mellitus / Q000209:etiology; D005006:Ethnicity; D005190:Family; D005260:Female; D058006:General Practice; D006470:Hemorrhage / Q000209:etiology; D006801:Humans; D007674:Kidney Diseases / Q000209:etiology; D008297:Male; D008875:Middle Aged; D058866:Osteoporotic Fractures / Q000209:etiology; D011446:Prospective Studies; D012306:Risk; D054556:Venous Thromboembolism / Q000209:etiology
keywords: Cprd; Prognosis; Qresearch; Qrisk2; Validation