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Osteoporos Int. 2020 Mar 17. doi: 10.1007/s00198-020-05376-2. [Epub ahead of print]

Repurposing a fracture risk calculator (FRAX) as a screening tool for women at risk for sarcopenia.

Author information

1
Institute for Mental and Physical Health and Clinical Translation (iMPACT), Deakin University, Geelong, Victoria, Australia. juliep@barwonhealth.org.au.
2
Department of Medicine - Western Health, The University of Melbourne, St Albans, Victoria, Australia. juliep@barwonhealth.org.au.
3
Department of Epidemiology and Preventive Medicine, Monash University, Prahran, Victoria, Australia. juliep@barwonhealth.org.au.
4
Barwon Health, Geelong, Victoria, Australia. juliep@barwonhealth.org.au.
5
Biostatistics Unit, Faculty of Health, Deakin University, Geelong, Victoria, Australia.
6
Institute for Mental and Physical Health and Clinical Translation (iMPACT), Deakin University, Geelong, Victoria, Australia.
7
Department of Medicine - Western Health, The University of Melbourne, St Albans, Victoria, Australia.
8
Barwon Health, Geelong, Victoria, Australia.

Abstract

Osteoporosis and sarcopenia share risk profiles, so we tested a fracture risk assessment tool (FRAX) as a screening tool for sarcopenia. FRAX probabilities without bone mineral density predicted sarcopenia with high sensitivity and reasonable specificity. There is potential to use this FRAX as a screening tool for sarcopenia.

PURPOSE:

There is a need for simple screening tools for sarcopenia. As osteoporosis and sarcopenia share risk profiles, we tested the performance of a fracture risk assessment tool for discriminating individuals at risk for sarcopenia.

METHODS:

In this longitudinal study, FRAX (Australia) probabilities were calculated for 354 women (ages 40-90 years) in the Geelong Osteoporosis Study. Sarcopenia was assessed a decade later using DXA-derived low appendicular lean mass (Lunar; ALM/height2 < 5.5 kg/m2) and low handgrip strength (Jamar; HGS < 16 kg), according to EWGSOP2. We determined FRAX probabilities (%) for hip fracture (HF-FRAX) and major osteoporotic fracture (MOF-FRAX), with and without BMD. Area under the receiver operator characteristic (AUROC) curves quantified the performance of FRAX for predicting sarcopenia.

RESULTS:

Baseline median (IQR) values for HF-FRAX without BMD were 0.4 (0.1-1.3) and for MOF-FRAX without BMD, 2.4 (1.2-5.2); comparable figures for HF-FRAX with BMD were 0.2 (0.0-0.7) and for MOF-FRAX with BMD, 2.1 (1.1-4.4). At follow-up, sarcopenia was identified for 11 (3.1%) women. When FRAX was calculated without BMD, the AUROC was 0.90 for HF-FRAX and 0.88 for MOF-FRAX. Optimal thresholds were 0.9 for HF-FRAX (sensitivity 90.9%, specificity 62.4%) and 5.3 for MOF-FRAX (sensitivity 81.8%, specificity 71.7%). Calculating FRAX with BMD did not improve the predictive performance of FRAX for sarcopenia.

CONCLUSION:

Here we provide preliminary evidence to suggest that FRAX probabilities without BMD might predict sarcopenia with high sensitivity and reasonable specificity. Given that FRAX clinical risk factors are identified without equipment, there is potential to use this or a modified version of the FRAX tool to screen for individuals at risk of sarcopenia.

KEYWORDS:

Lean mass; Muscle strength; Older women; Sarcopenia; Screening tool

PMID:
32185435
DOI:
10.1007/s00198-020-05376-2

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