title: [The role of biochemical markers of bone turnover in the diagnosis of osteoporosis and predicting fracture risk].
abstract: BACKGROUND
  Currently, for the diagnosis of osteoporosis, we search risk factors and measure bone mineral density (BMD) by DXA method. However, bone turnover markers, unused still in practice, have shown an interest especially in the prediction of fracture risk. aim: To determine the relationship between bone markers, BMD and osteoporotic fracture. methods: Prospective study of 65 women referred for measure of BMD during the period between May and August 2010. Each patient had a dosage of serum bone formation markers: osteocalcin (OC) and N-terminal propeptide of type I collagen (P1NP) and bone resorption markers: serum and urinary C-terminal telopeptide of type I collagen (β-CTX or CrossLaps) as well as parathyroid hormone and calcium. Risk factors of osteoporosis were identified in each case. results: Our 65 women had a mean age of 58.6 ± 12.1 years. The majority (83%) were menopausal women. Osteoporosis was found in 52%, osteopenia 26% and normal BMD 22% of cases. An increase in bone turnover markers was correlated with menopause (p = 0. 001 for the OC, p = 0.016 for urinary CTX), a low body mass index (p = 0.015 for OC, p = 0.042 for serum CTX) and osteoporosis (p <0.001 for P1NP, p <0.001 for serum and urinary CTX). Corticosteroid therapy was correlated with a decrease in bone formation markers (p = 0.002 for P1NP). The presence of fracture was only associated with increased urinary CTX (p = 0.05).
  
  
  CONCLUSIONS
  Bone turnover markers increase in menopausal women and in case of low BMD. However, their contribution in the diagnosis of osteoporosis is low. They are rather an interest in the prediction of fracture risk.
authors.forename: Younes
authors.initials: Y
authors.lastname: Mohamed
authors.forename: Hachfi
authors.initials: H
authors.lastname: Haifa
authors.forename: Ouertani
authors.initials: O
authors.lastname: Datel
authors.forename: Hassine Neffati
authors.initials: HN
authors.lastname: Fadoua
authors.forename: Ben Hammouda
authors.initials: BH
authors.lastname: Smeh
authors.forename: Jguirim
authors.initials: J
authors.lastname: Mahbouba
authors.forename: Zrour
authors.initials: Z
authors.lastname: Saoussen
authors.forename: Ismail
authors.initials: I
authors.lastname: Bejia
authors.forename: Touzi
authors.initials: T
authors.lastname: Mongi
authors.forename: Fadhel Najjar
authors.initials: FN
authors.lastname: Mohamed
authors.forename: Bergaoui
authors.initials: B
authors.lastname: Naceur
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015415:Biomarkers / Q000097:blood; D015519:Bone Density; D001851:Bone Diseases, Metabolic / Q000175:diagnosis; D016723:Bone Remodeling; D002118:Calcium / Q000097:blood; D024042:Collagen Type I / Q000097:blood / Q000652:urine; D005260:Female; D005938:Glucocorticoids / Q000009:adverse effects; D006801:Humans; D015994:Incidence; D008875:Middle Aged; D015675:Osteocalcin / Q000097:blood; D010024:Osteoporosis / Q000097:blood* / Q000175:diagnosis* / Q000453:epidemiology; D015663:Osteoporosis, Postmenopausal / Q000175:diagnosis; D058866:Osteoporotic Fractures / Q000097:blood / Q000517:prevention & control*; D010281:Parathyroid Hormone / Q000097:blood; D010446:Peptide Fragments / Q000097:blood; D010455:Peptides / Q000097:blood / Q000652:urine; D011347:Procollagen / Q000097:blood; D011446:Prospective Studies; D012307:Risk Factors; D014416:Tunisia / Q000453:epidemiology
chemical_list: D015415:Biomarkers; D024042:Collagen Type I; D005938:Glucocorticoids; D010281:Parathyroid Hormone; D010446:Peptide Fragments; D010455:Peptides; D011347:Procollagen; C052929:collagen type I trimeric cross-linked peptide; C047202:procollagen Type I N-terminal peptide; D015675:Osteocalcin; D002118:Calcium