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Meta-Analysis: Accuracy of Quantitative Ultrasound for Identifying Patients with Osteoporosis

Smita Nayak, MD; Ingram Olkin, PhD; Hau Liu, MD, MPH, MBA; Michael Grabe, PhD; Michael K. Gould, MD, MS; I. Elaine Allen, PhD; Douglas K. Owens, MD, MS; and Dena M. Bravata, MD, MS
[+] Article, Author, and Disclosure Information

From VA Palo Alto Health Care System, Palo Alto, California; Stanford University, Stanford, California; University of California, San Francisco, San Francisco, California; and Babson College, Babson Park, Massachusetts.

Acknowledgments: The authors thank Marilyn L. Tinsley, MLS, for assistance with the literature searches; David B. Karpf, MD, and Douglas C. Bauer, MD, for critical review of the manuscript; and Corinna Haberland, MD, MS, for contributions to data collection.

Grant Support: By a Department of Veterans Affairs Fellowship in Ambulatory Care Practice and Research (Dr. Nayak); by the Department of Veterans Affairs (Dr. Owens); by the Agency for Healthcare Research and Quality, National Research Service Award (grant number HS000028-18) (Dr. Liu); by a National Science Foundation Interdisciplinary Informatics Fellowship and the Howard Hughes Medical Institute (Dr. Grabe); and by an Advanced Research Career Development Award from the VA Health Services Research and Development Service (Dr. Gould).

Potential Financial Conflicts of Interest: None disclosed.

Requests for Single Reprints: Smita Nayak, MD, Center for Primary Care and Outcomes Research, Stanford University, 117 Encina Commons, Stanford, CA 94305-6019; e-mail, smitanayak@stanford.edu.

Current Author Addresses: Drs. Nayak, Liu, and Bravata: Center for Primary Care and Outcomes Research, Stanford University, 117 Encina Commons, Stanford, CA 94305-6019.

Dr. Olkin: Department of Statistics, Stanford University, Sequoia Hall, 390 Serra Mall, Stanford, CA 94305-4065.

Dr. Grabe: Department of Physiology and Biochemistry, Howard Hughes Medical Institute, University of California, San Francisco, 1550 4th Street, RH 482, San Francisco, CA 94143-0725.

Drs. Gould and Owens: VA Palo Alto Health Care System, 3801 Miranda Avenue, Palo Alto, CA 94304.

Dr. Allen: Babson College, 231 Forest Street, Babson Park, MA 02457.

Ann Intern Med. 2006;144(11):832-841. doi:10.7326/0003-4819-144-11-200606060-00009
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Background: There is increased interest in quantitative ultrasound for osteoporosis screening because it predicts fracture risk, is portable, and is relatively inexpensive. However, there is no consensus regarding its accuracy for identifying patients with osteoporosis.

Purpose: To determine the sensitivity and specificity of calcaneal quantitative ultrasound for identifying patients who meet the World Health Organization's diagnostic criteria for osteoporosis. Dual-energy x-ray absorptiometry (DXA) was used as the reference standard.

Data Sources: MEDLINE (1966 to October 2005), EMBASE (1993 to May 2004), Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews (1952 to March 2004), and the Science Citation Index (1945 to April 2004).

Study Selection: English-language articles that evaluated the sensitivity and specificity of calcaneal quantitative ultrasound for identifying adults with DXA T-scores of −2.5 or less at the hip or spine.

Data Extraction: Two authors independently reviewed articles and abstracted data.

Data Synthesis: The authors identified 1908 potentially relevant articles, of which 25 met the inclusion criteria, and calculated the sensitivity and specificity of quantitative ultrasound over a range of thresholds. For the quantitative ultrasound index parameter T-score cutoff threshold of −1, sensitivity was 79% (95% CI, 69% to 86%) and specificity was 58% (CI, 44% to 70%) for identifying individuals with DXA T-scores of −2.5 or less at the hip or spine. For a T-score threshold of 0, sensitivity improved to 93% (CI, 87% to 97%) but specificity decreased to 24% (CI, 10% to 47%). At a pretest probability of 22% (for example, a 65-year-old white woman at average risk), the post-test probability of DXA-determined osteoporosis was 34% (CI, 26% to 41%) after a positive result and 10% (CI, 5% to 12%) after a negative result when using a T-score cutoff threshold of −1. Analysis of other quantitative ultrasound parameters (for example, broadband ultrasound attenuation) revealed similar estimates of accuracy.

Limitations: The relatively small number of included studies limited the authors' ability to evaluate the effects of heterogeneous study characteristics on the diagnostic accuracy of quantitative ultrasound.

Conclusions: The currently available literature suggests that results of calcaneal quantitative ultrasound at commonly used cutoff thresholds do not definitively exclude or confirm DXA-determined osteoporosis. Additional research is needed before use of this test can be recommended in evidence-based screening programs for osteoporosis.


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Figure 1.
Literature search strategies and reasons for study exclusion.

The number of unique articles found from each database is shown in the top row of boxes. DXA = dual-energy x-ray absorptiometry. *MEDLINE search strategy: (osteoporo* AND ultraso*) OR (bone density AND ultraso*) OR (osteoporo* AND sonogra*). †EMBASE search strategy: ((osteoporosis/DE OR bone density/DE) OR (osteoporo? OR (bone density)) AND (ultrasound or ultrason? or sonogr?) AND (heel or calcaneus). ‡Science Citation Index search strategy: (osteoporo* <or> “bone density”) and (ultrasound <or> ultrason* <or> sonogra*) and (heel <or> calcan*). §Cochrane search strategy: (bone density.mp or osteoporosis.mp) and (ULTRASOUND or ultraso$ or sonogra$).mp and (heel or calcaneous or calcaneal).mp. ||Several articles met more than 1 of the exclusion criteria.

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Appendix Figure. The number of studies that fully met, did not meet, or did not report whether they met each criterion for the quantitative ultrasound index parameter ( ) and other parameters combined (broadband ultrasound attenuation, speed of sound, velocity of sound, and stiffness) ( ) is shown. The number of studies that fully met each criterion is shown to the right of 0, and the number of studies that did not meet each criterion or did not report whether they met each criterion is shown to the left of 0. DXA = dual-energy x-ray absorptiometry.
Results of assessment of potential sources of bias.topbottom
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Figure 2.
Results of meta-analysis of sensitivity versus threshold and specificity versus threshold for the quantitative ultrasound index parameter.topbottomtopbottom

The points represent summary estimates of sensitivity ( ) and specificity ( ) at particular T-score thresholds, obtained by using a random-effects meta-analysis model at each threshold. The bars represent 95% CIs. The solid lines represent regression models for sensitivity ( ) and specificity ( ) as functions of threshold. The dotted lines represent 95% CIs for the regression models.

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Figure 3.
Summary receiver-operating characteristic curve of sensitivity (true-positive rate) versus 1 − specificity (false-positive rate) for the quantitative ultrasound index parameter.

Individual study estimates of sensitivity and 1 − specificity are represented by the circles. Circle sizes are proportional to study weights; however, sizes are not to scale. The dotted lines represent 95% CIs.

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