XXXX risks and risk prediction models.

@entity43 @entity0 @entity5344 @entity5345 @entity5 @entity2674
@entity5345 /2 mutation carriers have a considerably increased risk to develop @entity5344 . The personalized clinical management of carriers and other at-risk individuals depends on precise knowledge of the @entity5 risks. In this report, we give an overview of the present literature on empirical @entity5 risks, and we describe risk prediction models that are currently used for individual risk assessment in clinical practice. @entity5 risks show large variability between studies. @entity0 risks are at 40-87% for @entity5345 mutation carriers and 18-88% for @entity2674 mutation carriers. For @entity43 , the risk estimates are in the range of 22-65% for @entity5345 and 10-35% for @entity2674 . The @entity0 risk is high (10-year risk after first @entity5 27% for @entity5345 and 19% for @entity2674 ). Risk prediction models have been proposed to provide more individualized risk prediction, using additional knowledge on family history, mode of inheritance of major genes, and other genetic and non-genetic risk factors. User-friendly software tools have been developed that serve as basis for decision-making in family counseling units. In conclusion, further assessment of @entity5 risks and model validation is needed, ideally based on prospective cohort studies. To obtain such data, clinical management of carriers and other at-risk individuals should always be accompanied by standardized scientific documentation.
