Age-modification risk models for IHD and stroke mortality.
Incorporating age-modification risk models tends to slightly decrease the PAF estimates.
A small modification of these models allows us to model a softer informational attitude.
However, our model can still indirectly incorporate changes in trends in risk factors by appropriate modification of model probabilities that relate to risk of certain CHD events (eg for people currently with no history of CHD).
The tested models include the Tyrer-Cuzick [ 20] and Gail [ 21] models, both of which include family history and non-familial risk factors, BOADICEA [ 22], a modification of the Claus model to include non-familial risk factors [ 23], the Rosner-Colditz model [ 24], and several others, many of which require further validation [ 16].
Multivariate risk models require careful attention to accurate measurements, a priori selection of the primary outcomes and risk factors of interest, specification of data collection including any missing values, and assessment of collinearity and any confounding or effect modification.
Attendees were advised on modification of ameliorable risk factors.
Here we will present one such modification of the model.
Second, modification of the UKPDS model to include a cardiovascular risk estimate of 2 for subjects with previous cardiovascular history, while based on published information on cardiovascular risk, requires validation (ie, patient-level data from specific studies).
The modification of the Gail model, by including breast density and the weight of the woman as risk factors, led to the model developed by Chen, et al. [ 11].
However, recent data have prompted a modification of this classic model.
