Clinical predictors of vertebral osteoporotic fractures in post-menopausal women: a cross-sectional analysis

Abstract

Background: Osteoporosis is a very common bone disorder and accounts for 1.4 million vertebral compression fractures (VCFs) per year, mostly in post-menopausal women.

Aim: The aim of this study was to develop a risk scoring system to identify and gauge the risk of osteoporotic VCFs in post-menopausal women.

Materials and methods: We conducted a retrospective cross-sectional study on 477 post-menopausal women consecutively visited at our institution. We studied 15 different clinical variables, i.e. age, body mass index (BMI), weight, L1-L4 lumbar T-Score, L1-L4 lumbar Z-Score, L1-L4 lumbar bone mineral density (BMD), femoral neck T-Score, femoral neck Z-Score, femoral neck BMD, smoking habit, alcohol consumption, 25-OH-vitamin D, total alkaline phosphatase, bone alkaline phosphatase, and L4 vertebral volume. Study population was split in a derivation and a validation cohort. A logistic regression model was used to develop a predictive score of osteoporotic VCFs in the derivation cohort, finally the performance of the score was tested in the validation cohort.

Results: Age, L1-L4 lumbar T-Score, femoral neck T-Score, L4 vertebral volume, and smoking habit were found to be predictors of VCFs. To each variable a score from 0 to +12 was assigned to the magnitude of regression coefficient. A score ≥ 22 identified VCFs with a sensitivity of 87%/89% and a specificity of 87%/90% in the derivation and validation cohorts, respectively.

Conclusions: Our findings indicate that a simple score derived from clinical history and routine diagnostic workout can be usefully employed to gauge the risk of fragility VCFs in post-menopausal women.