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Cover of Noninvasive Diagnostic Tests for Breast Abnormalities

Noninvasive Diagnostic Tests for Breast Abnormalities

Update of a 2006 Review

Comparative Effectiveness Reviews, No. 47

Investigators: Wendy Bruening, PhD, Stacey Uhl, MSS, Joann Fontanarosa, PhD, James Reston, PhD, MPH, Jonathan Treadwell, PhD, and Karen Schoelles, MD, SM, FACP.

ECRI Institute Evidence-based Practice Center
Rockville (MD): Agency for Healthcare Research and Quality (US); 2012 Feb.
Report No.: 12-EHC014-EF
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Structured Abstract

Objectives:

To systematically review the literature on the diagnostic accuracy of noninvasive imaging technologies proposed to be useful as part of the workup after recall of women with suspicious breast abnormalities identified on routine screening. This report is an update of a Comparative Effectiveness Review originally published in 2006.

Data Sources:

We searched the medical literature, including PubMed and Embase, from December 1994 through September 2010. We included diagnostic cohort studies that enrolled the patient population of interest and used current generation scanners and protocols of the noninvasive imaging technologies of interest. We excluded case-control studies, meeting presentations, and very small (<10 patients) studies.

Review Methods:

We abstracted data from the included studies and used a bivariate mixed-effects binomial regression model for meta-analysis. We used the summary likelihood ratios and Bayes’ theorem to calculate the post-test probability of having a benign or malignant lesion. We explored heterogeneity in the data with meta-regressions using standard methodology. We graded the strength of evidence supporting each major conclusion as high, moderate, low, or insufficient. The grade was developed by considering four important domains: the risk of bias in the evidence base (internal validity, or quality of the studies), the consistency of the findings, the precision of the results, and the directness of the evidence.

Results:

We identified 41 studies of magnetic resonance imaging (MRI). The summary sensitivity of MRI was 91.7 percent (95% CI: 88.5 to 94.1%) and the summary specificity was 77.5 percent (95% CI: 71.0 to 82.9%). The estimate of accuracy was judged to be supported by a moderate to low strength of evidence (low for the estimate of specificity due to the lack of precision as reflected in the wide confidence interval). Bayes’ theorem and the summary estimates of accuracy suggest that only women with a pre-MRI suspicion of malignancy of 12 percent or less will have their post-MRI suspicion of malignancy change sufficiently to suggest that a change in patient management may be appropriate.

We identified seven studies of positron emission tomography (PET). The summary sensitivity of PET was 83.0 percent (95% CI: 73.0 to 89.0%) and the summary specificity was 74.0 percent (95% CI: 58.0 to 86.0%). The estimate of accuracy was judged to be supported by a Low strength of evidence. Bayes’ theorem and the summary estimates of accuracy suggest that only women with a pre-PET suspicion of malignancy of 5 percent or less will have their post-PET suspicion of malignancy change sufficiently to suggest that a change in patient management may be appropriate.

We identified 10 studies of scintimammography. The summary sensitivity of scintimammography was 84.7 percent (95% CI: 78.0 to 89.7%) and the summary specificity was 77.0 percent (95% CI: 64.7 to 85.9%). The estimate of accuracy was judged to be supported by a Low strength of evidence. Bayes’ theorem and the summary estimates of accuracy suggest that only women with a pre-scintimammography suspicion of malignancy of 5 percent or less will have their post-scintimammography suspicion of malignancy change sufficiently to suggest that a change in patient management may be appropriate.

We identified 21 studies of B-mode grayscale ultrasound, six studies of color Doppler ultrasound, and seven studies of power Doppler ultrasound. For B-mode grayscale, summary sensitivity was 92.4 percent (95% CI: 84.6 to 96.4%) and the summary specificity was 75.8 percent (95% CI: 60.8 to 86.3%); for color Doppler, summary sensitivity was 88.5 percent (95% CI: 74.4 to 95.4%) and summary specificity was 76.4 percent (95% CI: 61.7 to 86.7%); for power Doppler, summary sensitivity was 70.8 percent (95% CI: 47 to 86.6%) and summary specificity was 72.6 percent (95% CI: 59.9 to 82.5%). These estimates of accuracy were all judged to be supported by a Low strength of evidence. Bayes’ theorem and the summary estimates of accuracy suggest that only women with a pre-ultrasound suspicion of malignancy of 10 percent or less will have their post-ultrasound suspicion of malignancy change sufficiently to suggest that a change in patient management may be appropriate.

Conclusions:

The use of noninvasive imaging, in addition to standard workup of women recalled for evaluation of an abnormality detected on breast cancer screening, may be clinically useful for diagnostic purposes only for women with a low (less than 12%) pretest suspicion of malignancy. When choosing which noninvasive imaging technology to use for this purpose, the evidence appears to suggest that diagnostic B-mode grayscale ultrasound and MRI are more accurate than PET, scintimammography, or Doppler ultrasound. The utility of these findings, however, depend on whether clinicians can identify women with a pretest suspicion of malignancy in the ranges necessary for the tests to affect management. Several of the expert reviewers of this report did not think this is currently possible.

Contents

Prepared for: Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services1, Contract No. 290-02-0019, Prepared by: ECRI Institute Evidence-based Practice Center, Plymouth Meeting, PA

Suggested citation:

Bruening W, Uhl S, Fontanarosa J, Reston J, Treadwell J, Schoelles K. Noninvasive Diagnostic Tests for Breast Abnormalities: Update of a 2006 Review. Comparative Effectiveness Review No. 47. (Prepared by the ECRI Institute Evidence-based Practice Center under Contract No. 290-02-0019.) AHRQ Publication No. 12-EHC014-EF. Rockville, MD: Agency for Healthcare Research and Quality; February 2012. www.effectivehealthcare.ahrq.gov/reports/final.cfm.

This report is based on research conducted by the ECRI Institute Evidence-based Practice Center (EPC) under contract to the Agency for Healthcare Research and Quality (AHRQ), Rockville, MD (Contract No. 290-02-0019). The findings and conclusions in this document are those of the author(s), who are responsible for its contents; the findings and conclusions do not necessarily represent the views of AHRQ. Therefore, no statement in this report should be construed as an official position of AHRQ or of the U.S. Department of Health and Human Services.

The information in this report is intended to help healthcare decisionmakers—patients and clinicians, health system leaders, and policymakers, among others—make well-informed decisions and thereby improve the quality of health care services. This report is not intended to be a substitute for the application of clinical judgment. Anyone who makes decisions concerning the provision of clinical care should consider this report in the same way as any medical reference and in conjunction with all other pertinent information, i.e., in the context of available resources and circumstances presented by individual patients.

This report may be used, in whole or in part, as the basis for the development of clinical practice guidelines and other quality enhancement tools, or as a basis for reimbursement and coverage policies. AHRQ or U.S. Department of Health and Human Services endorsement of such derivative products may not be stated or implied.

None of the investigators has any affiliations or financial involvement that conflicts with the material presented in this report.

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