FRAXModell

FRAXmodell is a predictive algorithm used to calculate the risk of osteoporotic fractures based on clinical risk factors. It takes into account several factors such as age, sex, highest bone mass index, weight, height, smoking status, glucocorticoid therapy, secondary osteoporosis, and family history of hip fractures.

The FRAX algorithm was developed by a team of researchers at the University of Sheffield in the UK, led by John A. Kanis. The first version of the FRAX model was published in 2008 and has since undergone several updates and revisions. The model is widely used by healthcare professionals and organizations across the globe to assess the risk of osteoporotic fractures in postmenopausal women and men over the age of 50.

FRAXmodell is based on a Bayesian probability approach, which allows it to incorporate clinical risk factors in a probabilistic manner. The model estimates the 10-year probability of hip fracture and major osteoporotic (clinical spine, hip, wrist, and forearm) fracture, as well as the absolute risk of these outcomes. The output of the model can be used to guide treatment decisions, such as the initiation of osteoporosis therapy and the assessment of fracture risk in menopausal women.

The validity and reliability of FRAXmodell have been extensively tested and validated in various populations. While it has been widely adopted and used in clinical practice, some researchers have raised concerns about the model's reliance on clinical risk factors and its inability to take into account certain lifestyle and environmental factors that may also contribute to osteoporosis risk. Nevertheless, FRAXmodell remains a valuable tool for healthcare professionals seeking to estimate the risk of osteoporotic fractures in their patients.