Article Text

PDF
AB0796 The Predictors of Fracture in Patients with Hyperparathyroidism: An Observational Study
  1. S. Ashraf1,
  2. B. Khan1,
  3. R. Sinha2,
  4. M. Bukhari2
  1. 1Lancaster University
  2. 2Rheumatology, Royal Lancaster Infirmary, Lancaster, United Kingdom

Abstract

Background Hyperparathyroidism and other endocrine disorders have been associated with a low bone mineral density. The FRAX ™ tool uses the femoral neck to predict fractures on a population basis and ignores the lumbar spine.

Objectives We set out to determine the predictors of fragility fractures in a large cross sectional study of 508 patients diagnosed with Hyperparathyroidism.

Methods Patients referred for bone mineral density (BMD) estimation in a scanner in the North West of England with a history of Hyperparathyroidism were identified from a dual X-ray absorptiometry (DEXA) database. Demographics and other risk factors were recorded as well as fragility fractures. Initially, Univariate logistic regression models were modelled predicting fractures in the data set and a multivariate model was subsequently fitted. Variables included age at scan, gender, body mass index (BMI), family history of fracture, alcohol intake, smoking, glucocorticoid exposure, rheumatoid arthritis, in addition to BMD in the lumbar spine and femoral neck.

Results 508 patients were scanned in the referral period. Mean age at scan was 65.0 (SD 12.4). 411 (80.9%) of the patients were female and 97 were male. Results of the univariate analysis (adjusted for age and gender) are shown in table 1. Significant predictors are denoted with an asterisk.

Table 1

In the multivariate model, the only variable that predicted fractures in this cohort was Lumbar spine BMD OR 0.18 (95% CI 0.31,1.04)

Conclusions In the univariate analysis, many risk factors are associated with fracture. However in the multivariate analysis conducted, the best predictor was Lumbar Spine BMD. This is not included in the FRAX ™ tool and would make estimating the fracture risk in this cohort difficult. Further modelling in other cohorts is needed to validate this finding.

Disclosure of Interest None declared

Statistics from Altmetric.com

Request permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.