Calcified Tissue International

, Volume 93, Issue 1, pp 62–68

Reducing the Need for Central Dual-Energy X-Ray Absorptiometry in Postmenopausal Women: Efficacy of a Clinical Algorithm Including Peripheral Densitometry

Authors

  • Francisco Gabriel Jiménez-Núñez
    • Rheumatology ServiceHospital Regional Universitario Carlos Haya
    • Rheumatology ServiceHospital Regional Universitario Carlos Haya
  • Inmaculada Ureña-Garnica
    • Rheumatology ServiceHospital Regional Universitario Carlos Haya
  • Carmen María Romero-Barco
    • Rheumatology ServiceHospital Regional Universitario Carlos Haya
  • Blanca Panero-Lamothe
    • Rheumatology ServiceHospital Regional Universitario Carlos Haya
  • Miguel Ángel Descalzo
    • Research UnitFundación Española de Reumatología
  • Loreto Carmona
    • Health Sciences SchoolUniversidad Camilo José Cela
  • Manuel Rodríguez-Pérez
    • Rheumatology ServiceHospital Regional Universitario Carlos Haya
  • Antonio Fernández-Nebro
    • Rheumatology ServiceHospital Regional Universitario Carlos Haya
Original Research

DOI: 10.1007/s00223-013-9728-4

Cite this article as:
Jiménez-Núñez, F.G., Manrique-Arija, S., Ureña-Garnica, I. et al. Calcif Tissue Int (2013) 93: 62. doi:10.1007/s00223-013-9728-4

Abstract

We evaluated the efficacy of a triage approach based on a combination of osteoporosis risk-assessment tools plus peripheral densitometry to identify low bone density accurately enough to be useful for clinical decision making in postmenopausal women. We conducted a cross-sectional diagnostic study in postmenopausal Caucasian women from primary and tertiary care. All women underwent dual-energy X-ray absorptiometric (DXA) measurement at the hip and lumbar spine and were categorized as osteoporotic or not. Additionally, patients had a nondominant heel densitometry performed with a PIXI densitometer. Four osteoporosis risk scores were tested: SCORE, ORAI, OST, and OSIRIS. All measurements were cross-blinded. We estimated the area under the curve (AUC) to predict the DXA results of 16 combinations of PIXI plus risk scores. A formula including the best combination was derived from a regression model and its predictability estimated. We included 505 women, in whom the prevalence of osteoporosis was 20 %, similar in both settings. The best algorithm was a combination of PIXI + OST + SCORE with an AUC of 0.826 (95 % CI 0.782–0.869). The proposed formula is Risk = (–12) × [PIXI + (−5)] × [OST + (−2)] × SCORE and showed little bias in the estimation (0.0016). If the formula had been implemented and the intermediate risk cutoff set at −5 to 20, the system would have saved €4,606.34 in the study year. The formula proposed, derived from previously validated risk scores plus a peripheral bone density measurement, can be used reliably in primary care to avoid unnecessary central DXA measurements in postmenopausal women.

Keywords

Bone density DEXA Osteoporosis Diagnosis

Copyright information

© Springer Science+Business Media New York 2013