DENSITY OF LUMBAR VERTEBRAE - RISK-FACTOR S FOR VERTEBRAL FRACTURES IN WOMEN

Background and objective: The direct connections between a reduction i n bone density and an increase in the incidence of fractures with incr easing age is well known. When interpreting bone density measurements the attending physician is confronted with an overlap of false-positiv e and false-negative parameters, as is also the case with biochemical data. Aim of this study was to determine, in addition to bone density, a fracture threshold, i.e. a value for bone density with maximal sens itivity and specificity, ina representative cohort of women. Patients and methods: 534 healthy women (mean age 60.9 +/- 8.07, range 40-83 ye ars), seen in an out-patient osteological clinic between 1993 and 1996 were included. After full biochemical investigation to exclude a meta bolic bone disease, bone density (LBD) of the lumbar vertebrae 1-5 and the number of vertebral body fractures were documented, together with age and menopausal status. LED was measured by quantitative computed tomography (qCT), results being analysed with the Wilcoxon 2-sample te st and logistic regression and assessed by receiver operating characte ristics (ROC) analysis. Results: None of the women with a qCT value ov er 111 mg/cc had evidence of vertebral fractures. Those with values un der 60 mg/cc had at least one vertebral fracture (defined as at least 15% reduction in vertebral body height). There was a highly significan t negative correlation between age and LED (r = -0.56; P < 0.0001), as well as between LED and the number of fractured vertebrae (r = -0.58, P < 0.0001). But there was no longer any correlation between age and number of vertebral body fractures once allowance was made for LED (r = 0.001, not significant). The least overlap of false-positive and fal se-negative values was at an LED with qCT values of 102 mg/cc. Conclus ions: LED is the determining variable for fracture risk independent of age. Despite an overlap of false-positive and false-negative LED valu es, the probability of fractures can be predicted from bone mineral co ntent.