title: Bone turnover rate in postmenopausal women: bimodal distribution?
abstract: There is considerable evidence that elevated bone turnover is an independent form of low bone mineral density (BMD) risk factor of osteoporotic fractures. The aim of our study was to test whether a group of postmenopausal women could be divided into subgroups of high and low bone turnover rate using different pairs of bone turnover markers (one resorption, one formation). Cluster analysis was used to obtain high and low bone turnover subgroups within the study group. A magnitude of difference in lumbar spine BMD (expressed as Z-score) between high- and low-turnover groups was used as a criterion of division success. According to this criterion, the division obtained with a urinary type I collagen crosslinked N-telopeptide/bone alkaline phosphatase pair of markers appeared to be the most significant. This method of separation of two subgroups was highly concordant with the division based on the upper thresholds of the normal values for those markers found for the premenopausal women. It seems that the observed existence of high-and low-turnover subject clusters is not an incidental phenomenon, because the effects obtained for the whole study group were further confirmed by the consistent results of cluster analysis, performed separately for two randomly selected subgroups (A and B) from the study group. The results obtained appear to support the view that bone turnover rate in postmenopausal women is distributed in the bimodal fashion. This finding seems to justify further investigations of more elaborated models, enabling clinicians to individually classify their patients as low- or high-turnover cases with higher efficiency, as in the case of cutoff values for single markers.
authors.affiliation: The Children's Memorial Health Institute, Warszawa-Miedzylesie, Poland.
authors.forename: J
authors.initials: J
authors.lastname: Łukaszkiewicz
authors.forename: E
authors.initials: E
authors.lastname: Karczmarewics
authors.forename: J
authors.initials: J
authors.lastname: Marowska
authors.forename: M
authors.initials: M
authors.lastname: Kóbylińska
authors.forename: K
authors.initials: K
authors.lastname: Prószyńska
authors.forename: L
authors.initials: L
authors.lastname: Bielecka
authors.forename: H
authors.initials: H
authors.lastname: Matusik
authors.forename: P
authors.initials: P
authors.lastname: Płudowski
authors.forename: K
authors.initials: K
authors.lastname: Hoszowski
authors.forename: P
authors.initials: P
authors.lastname: Korczyk
authors.forename: W
authors.initials: W
authors.lastname: Tłustochowicz
authors.forename: J
authors.initials: J
authors.lastname: Lorenc
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000469:Alkaline Phosphatase / Q000032:analysis; D015519:Bone Density; D016723:Bone Remodeling; D001842:Bone and Bones / Q000201:enzymology; D016000:Cluster Analysis; D003094:Collagen / Q000652:urine; D024042:Collagen Type I; D005260:Female; D006801:Humans; D008875:Middle Aged; D010455:Peptides / Q000652:urine; D010865:Pilot Projects; D017698:Postmenopause / Q000502:physiology*
chemical_list: D024042:Collagen Type I; D010455:Peptides; C052929:collagen type I trimeric cross-linked peptide; D003094:Collagen; D000469:Alkaline Phosphatase