OBJECTIVE: Various @entity65 models have been developed for @entity1 with @entity164 2 @entity6 . Their predictive performance in new @entity1 is mostly not investigated. This study aims to quantify the predictive performance of all @entity65 models developed specifically for @entity6 @entity1 . DESIGN AND METHODS: Follow-up data of 453, 1174 and 584 @entity164 2 @entity6 @entity1 without pre-existing @entity65 ( @entity65 ) in the EPIC-NL, EPIC-Potsdam and Secondary Manifestations of @entity455 cohorts, respectively, were used to validate 10 prediction models to estimate risk of @entity65 or @entity301 ( @entity301 ). Discrimination was assessed by the c-statistic for time-to-event data. Calibration was assessed by calibration plots, the Hosmer-Lemeshow goodness-of-fit statistic and expected to observed ratios. RESULTS: There was a large variation in performance of @entity65 and @entity301 scores between different cohorts. Discrimination was moderate for all 10 prediction models, with c-statistics ranging from 0.54 (95% CI 0.46 to 0.63) to 0.76 (95% CI 0.67 to 0.84). Calibration of the original models was poor. After simple recalibration to the disease incidence of the target populations, predicted and observed risks were close. Expected to observed ratios of the recalibrated models ranged from 1.06 (95% CI 0.81 to 1.40) to 1.55 (95% CI 0.95 to 2.54), mainly driven by an overestimation of risk in high-risk @entity1 . CONCLUSIONS: All 10 evaluated models had a comparable and moderate discriminative ability. The recalibrated, but not the original, prediction models provided accurate risk estimates. These models can assist clinicians in identifying @entity164 2 @entity6 @entity1 who are at low or high risk of developing @entity65 .

The validation of cardiovascular risk scores for XXXX with @entity6 .

@entity1 :: ('9606', 'Species') :: ['patients'] @entity455 :: ('MESH:D014652', 'Disease') :: ['ARTerial disease'] @entity6 :: ('MESH:D003920', 'Disease') :: ['diabetes'] @entity301 :: ('MESH:D003327', 'Disease') :: ['CHD', 'coronary heart disease'] @entity164 :: ('MESH:D017827', 'Disease') :: ['type'] @entity65 :: ('MESH:D002318', 'Disease') :: ['cardiovascular prediction', 'CVD', 'cardiovascular disease']
@entity1 :: (9606,Species) :: ['patients']
