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Cost effectiveness of ultrasound and bone densitometry for osteoporosis screening in post-menopausal women

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Abstract

Background

According to a new German guideline, decisions about bisphosphonate treatment for post-menopausal women should be based on 10-year fracture risk, and bone density should be measured by dual x-ray absorptiometry (DXA). Recently, there has been growing interest in quantitative ultrasound (QUS) as a less expensive screening alternative.

Objective

To determine the cost effectiveness of osteoporosis screening with QUS as a pre-test for DXA and treatment with alendronate compared with (i) immediate access to DXA and (ii) no screening in women of the general population aged 50-90 years in Germany.

Methods

A cost-utility analysis and a budget impact analysis were performed from the perspective of the statutory health insurance (SHI). A Markov model with a 1-year cycle length was used to simulate costs and benefits (QALYs), discounted at 3% per annum, over a lifetime. The number of women correctly diagnosed by QUS and DXA as being above a 10-year risk of ≥30% was estimated for different age groups (50–60, 60–70, 70–80 and 80–90 years, respectively). The robustness of the results was tested by a probabilistic Monte Carlo simulation.

Results

Compared with no screening, the cost effectiveness of QUS plus DXA was found to be €3529, €9983, €4382 and €1987 per QALY for 50-, 60-, 70- and 80-year-old women, respectively (year 2006 values). This screening strategy results in annual costs of €96 million or 0.07% of the SHI’s annual budget. The cost effectiveness of DXA alone compared with DXA plus QUS is €5331, €60 804, €14943 and €3654 per QALY for 50-, 60-, 70- and 80-year-old women, respectively. DXA alone results in a higher number of QALYs in all age groups. The results were robust in the sensitivity analysis.

Conclusion

Compared with no screening, the cost effectiveness of QUS and DXA in sequence is very favourable in all age groups. However, direct access to DXA is also a cost-effective option, as it increases the number of QALYs at an acceptable cost compared with pre-testing by QUS (except for women aged 60–70 years). Therefore, QUS as a pre-test for DXA can be clearly recommended only in women aged 60–70 years. For the other age groups, the cost effectiveness of QUS as a pre-test depends on the global budget constraint and the accessibility of DXA.

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Acknowledgements

No sources of funding were used to assist in the preparation of this study. The authors have no conflicts of interest that are directly relevant to the content of this article.

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Authors and Affiliations

  1. Institute of Health Economics and Clinical Epidemiology, University of Cologne, Cologne, Germany

    Dirk Mueller &  Afschin Gandjour

  2. Department of Health Care Management, University of Cologne, Albertus-Magnus Platz, Cologne, 50923, Germany

    Dirk Mueller

  3. The James A. Baker III Institute for Public Policy, Rice University MS-40, P.O. Box 1892, Houston, TX, 77251-1892, USA

    Afschin Gandjour

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  1. Dirk Mueller
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Correspondence to Dirk Mueller or Afschin Gandjour.

Appendix

Appendix

Search Strategies in PubMed

Search strategy for medical interventions

  1. 1.

    Osteoporosis [MeSH]

  2. 2.

    Bone density [MeSH]

  3. 3.

    Fractures, bone [MeSH]

  4. 4.

    Alendronate [MeSH]

  5. 5.

    #1 OR #2 OR #3

  6. 6.

    #4 AND #5 (1136)

  7. 7.

    #4 AND #5 Limits: English, German, Meta-Analysis, Randomized Controlled Trial (274).

  8. 8.

    Osteoporosis [MeSH].

Search strategy for HR-QOL and fracture risks:

  1. 1.

    Osteoporosis [MeSH]

  2. 2.

    Osteoporotic fracture* [TIAB]

  3. 3.

    Spinal fractures [MeSH]

  4. 4.

    Radius fractures [MeSH]

  5. 5.

    Ulna fractures [MeSH]

  6. 6.

    Hip fractures [MeSH]

  7. 7.

    Mortality [subheading]

  8. 8.

    Increased risk [TIAB]

  9. 9.

    Quality-adjusted life years [MeSH]

  10. 10.

    #1 OR #2 OR #3 OR #4 OR #5 OR #6

  11. 11.

    #7 OR #8

  12. 12.

    #9 AND #10 (61)

  13. 13.

    #10 AND #11 (2348)

  14. 14.

    #10 AND #11 Limits: Middle Aged + Aged: 45 +years, English, German (1635).

Trials Included in the Analysis

Inclusion criteria for clinical trials are listed in table AI. Further information on the trials included in the analysis is provided in table AII.

Formulae to Calculate Average Risk

The average risk in the high-risk populations of our model was calculated using a mathematical model developed by De Laet et al.[45] The proportion of individuals (P) above the risk threshold (RT) of 30% was calculated based on the ratio of the risk threshold to the average population risk (AR) of each age group and a gradient of risk (GR) of 3.0. On the assumption that the combination of risk factors is distributed normally or close to normally in the population, the proportion of women above the threshold is (equation 2):

$$P=\Phi[z]$$
(2)

where Φ is the cumulative distribution function of the standardized normal distribution, and z is given by (equation 3):

$$\rm z=-[1n(RT/AR)+(1n(GR))^2/2]/1n(GR)$$
(3)

The average risk in women above the threshold (ART) relative to the average risk in the general population is determined by equation 4:

$$\rm AR_T={\Phi(z+1n(GR))\over \Phi(z)}$$
(4)
Table AI
figure Tab5

Inclusion criteria for clinical trials

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Table All
figure Tab6

Data on clinical effectiveness (vertebral, hip and forearm fractures)

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Mueller, D., Gandjour, A. Cost effectiveness of ultrasound and bone densitometry for osteoporosis screening in post-menopausal women. Appl Health Econ Health Policy 6, 113–135 (2008). https://doi.org/10.1007/BF03256127

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