title: The external validation of the cardiovascular risk equation for renal transplant recipients: applications to BENEFIT and BENEFIT-EXT trials.
abstract: BACKGROUND
  Renal transplant recipients (RTRs) have increased cardiovascular disease risk. Recently, major adverse cardiac event (MACE) and mortality risk calculators for prevalent RTRs were developed. We aimed to externally validate these risk equations in an international transplant database and subsequently demonstrate application to 2 clinical trials: Belatacept Evaluation of Nephroprotection and Efficacy as First-line Immunosuppression Trial (BENEFIT) and Belatacept Evaluation of Nephroprotection and Efficacy as First-line Immunosuppression Trial-EXTended criteria donors (BENEFIT-EXT).
  
  
  METHODS
  The 7-year risk calculators were developed using data from the ALERT trial and validated for discrimination and calibration in the Patient Outcomes in Renal Transplantation (PORT) study cohort. The outlier laboratory readings were trimmed to the 99th percentile observed in the PORT database. Diabetes mellitus, LDL-cholesterol, and serum creatinine values 3 years posttransplantation were used when applying the calculators to BENEFIT and BENEFIT-EXT trial treatment arms.
  
  
  RESULTS
  MACE could be predicted using a 7-variable model. The area under the ROC curve was 0.738 in ALERT and 0.740 in PORT, indicating preserved discrimination. In PORT, the calibration of the model indicated significant underestimation of risk in decile 5 and 9. Total mortality could be predicted using a 6-variable model. The area under the ROC curve was 0.734 in ALERT and 0.721 in PORT, indicating preserved discrimination. In PORT, the calibration of the model indicated significant underestimation of risk in decile 7 and significant overestimation in the highest risk decile. In BENEFIT and BENEFIT-EXT trial, the calculator estimated that belatacept use may result in reduction in MACE (>20%) and mortality (∼18%-30%).
  
  
  CONCLUSIONS
  The MACE and mortality risk calculators for prevalent RTRs have been externally validated and found suitable for generic risk stratification.
authors.affiliation: Department of Medical Sciences, Uppsala University, Uppsala, Sweden. inga.soveri@medsci.uu.se
authors.forename: Inga
authors.initials: I
authors.lastname: Soveri
authors.forename: Jon
authors.initials: J
authors.lastname: Snyder
authors.forename: Hallvard
authors.initials: H
authors.lastname: Holdaas
authors.forename: Ingar
authors.initials: I
authors.lastname: Holme
authors.forename: Alan G
authors.initials: AG
authors.lastname: Jardine
authors.forename: Gilbert J
authors.initials: GJ
authors.lastname: L'Italien
authors.forename: Bengt
authors.initials: B
authors.lastname: Fellström
mesh_terms: D000328:Adult; D002318:Cardiovascular Diseases / Q000209:etiology*; D005260:Female; D006801:Humans; D016030:Kidney Transplantation / Q000009:adverse effects*; D008297:Male; D008875:Middle Aged; D012372:ROC Curve; D012307:Risk Factors