Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 2 de 2
Filter
Add more filters










Database
Publication year range
1.
Maturitas ; 106: 1-7, 2017 Dec.
Article in English | MEDLINE | ID: mdl-29150162

ABSTRACT

OBJECTIVES: The estimation of fracture risk using clinical risk factors (CRFs) is of primary concern in osteoporosis management, but only some risk factors have been thoroughly evaluated and incorporated in predictive models. We have launched a large prospective study, the 'Fracture Risk Brussels Epidemiological Enquiry' (FRISBEE), to develop a new predictive model for osteoporotic fractures. The aims of this report are to describe the methodology of the FRISBEE study and to compare the distribution of CRFs in our cohort with those reported in other large studies. STUDY DESIGN: FRISBEE is a new study that prospectively evaluates a cohort of 3560 post-menopausal women (aged 60-85 years) followed yearly for the occurrence of fragility fractures. Multiple validated CRFs, densitometry (DXA) values and intake of medication were systematically registered at baseline. The distribution of the FRISBEE CRFs has been compared with the distributions of CRFs in the cohorts used to develop the FRAX® model as well as in more recent cohorts. For these recent cohorts, we focused on CRFs not included in FRAX®. RESULTS: The most frequently encountered CRFs used in FRAX® were a prior fragility fracture (27.1%) and a parental history of hip fracture (13.4%). The prevalence of some CRFs not integrated in FRAX® was relatively high, such as the use of proton pump inhibitors (20.8%) and a history of fall(s) (19.7%). The prevalence of many CRFs was quite variable between cohorts; for example, the prevalence of 'personal prior fragility fracture' ranged from 9% to 51%. CONCLUSION: We found considerable heterogeneity in the prevalence of CRFs between cohort studies. The impact of these differences on the predictive value of a particular CRF is unknown. We will construct a predictive model calibrated to the Belgian population. More importantly, the FRISBEE study should allow us to determine the predictive value of newly recognized CRFs in addition to the FRAX® algorithm to reliably estimate fracture risk.


Subject(s)
Osteoporotic Fractures/epidemiology , Accidental Falls , Aged , Aged, 80 and over , Algorithms , Belgium/epidemiology , Female , Humans , Middle Aged , Postmenopause , Prevalence , Prospective Studies , Risk Factors
2.
Rev Med Brux ; 29(4): 289-93, 2008 Sep.
Article in French | MEDLINE | ID: mdl-18949979

ABSTRACT

Osteoporosis is a major public health problem. For the time being, the diagnosis of osteoporosis relies on densitometry (T-score < -2.5 by DXA), although the risk of fracture depends also on other factors than the bone mass. Osteoporosis diagnosis (DXA) must be distinguished from the individual risk assessment of fracture. Different risk factors complementary to bone mass have been already validated in different populations. These include an old age, a history of fracture after the age of 50, a familial history of hip fracture (father or mother), a low BMI (< 20), corticoid treatment (> 3 months), tabagism and excessive alcohol consumption. A WHO taskforce has combined these different factors in order to integrate them in a 10-years predictive risk model of fracture (FRAX**). This model should still be validated in different populations, especially in populations not included in its development, which is the case for Belgium. We are evaluating these different risk factors for fracture in a Brussels population of 5000 women (60-80 years) who will be followed each year during 10 years. We also assess the predictive value of other risk factors for fracture not included in the WHO model (tendency to fall, use of sleeping pills, early non substituted menopause, sedentarity, ...). In an interim analysis of the first 452 women included and with data yet available at the time of this writing, we could find a significant (P < 0.05) relationship between diagnosis of osteoporosis at DXA and the number of risk factors, age > 70 years, a personal history of fracture after 50 years and a BMI < 20.


Subject(s)
Fractures, Bone/epidemiology , Osteoporosis/epidemiology , Accidental Falls/statistics & numerical data , Aged , Aged, 80 and over , Belgium/epidemiology , Body Mass Index , Cohort Studies , Female , Follow-Up Studies , Humans , Menopause , Middle Aged , Osteoporosis/complications , Predictive Value of Tests , Prevalence , Risk Factors
SELECTION OF CITATIONS
SEARCH DETAIL
...