False positive mammograms and detection controlled estimation

Leveraging system sciences methods in clinical trial evaluation: An example concerning African American women diagnosed with breast cancer via the Patient Navigation in Medically Underserved Areas study

BACKGROUND

Systems science methodologies offer a promising assessment approach for clinical trials by: 1) providing an in-silico laboratory to conduct investigations where purely empirical research may be infeasible or unethical; and, 2) offering a more precise measurement of intervention benefits across individual, network, and population levels. We propose to assess the potential of systems sciences methodologies by quantifying the spillover effects of randomized controlled trial via empirical social network analysis and agent-based models (ABM).

DESIGN/METHODS

We will evaluate the effects of the Patient Navigation in Medically Underserved Areas (PNMUA) study on adult African American participants diagnosed with breast cancer and their networks through social network analysis and agent-based modeling. First, we will survey 100 original trial participants (50 navigated, 50 non-navigated) and 150 of members of their social networks (75 from navigated, 75 non-navigated) to assess if navigation results in: 1) greater dissemination of breast health information and breast healthcare utilization throughout the trial participants' networks; and, 2) lower incremental costs, when incorporating navigation effects on trial participants and network members. Second, we will compare cost-effectiveness models, using a provider perspective, incorporating effects on trial participants versus trial participants and network members. Third, we will develop an ABM platform, parameterized using published data sources and PNMUA data, to examine if navigation increases the proportion of early stage breast cancer diagnoses.

DISCUSSION

Our study results will provide promising venues for leveraging systems science methodologies in clinical trial evaluation.

Specialized Second Opinion Interpretations of Breast Imaging: Impact on Additional Workup and Management

BACKGROUND

Women with breast imaging often seek second opinions at tertiary care centers. Our study measures the frequency of discrepancy between initial and second opinion breast imaging recommendations and evaluates the impact on patient management.

MATERIALS AND METHODS

A retrospective chart review was conducted on 504 consecutive patients with second opinion breast radiology interpretations performed by 6 sub-specialized breast radiologists at a dedicated cancer center from January 1, 2014 through September 1, 2014. Outside imaging reports were compared with second opinion reports to categorize discrepancies. Interpretations were considered discrepant in cases with Breast Imaging Reporting and Data System (BI-RADS) category changes, recommendation for additional imaging, or identification of previously undiagnosed additional extent of disease greater than 5 cm. The frequencies of discrepancy, alterations in surgical management, and incremental cancer detection were measured. Statistical analysis of associated factors was performed with the Fisher exact test, with a P-value < .05 considered significant.

RESULTS

Second opinion evaluation discrepancies were seen in 287 (57%) patients and resulted in percutaneous image-guided biopsies in 92 (18%). Forty-five additional sites of cancer were biopsy-detected in 41 (8%) patients, including 20 breast malignancies and 25 axillary metastases. Another 9 biopsies yielded high-risk pathology. Second opinion interpretations altered surgical management in 66 (13%) patients. Factors associated with increased discrepancy frequency were cancer diagnosis at presentation (P = .004), dense breasts (P = .005), and the absence of prior studies for comparison (P = .007).

CONCLUSION

Although additional imaging and resources are required, second opinion radiology review by subspecialized breast radiologists increases cancer detection and results in clinically relevant changes in patient management.

The Economic and Social Value of an Image Exchange Network: A Case for the Cloud

As the health care environment continually changes, radiologists look to the ACR's Imaging 3.0^® initiative to guide the search for value. By leveraging new technology, a cloud-based image exchange network could provide secure universal access to prior images, which were previously siloed, to facilitate accurate interpretation, improved outcomes, and reduced costs. The breast imaging department represents a viable starting point given the robust data supporting the benefit of access to prior imaging studies, existing infrastructure for image sharing, and the current workflow reliance on prior images. This concept is scalable not only to the remainder of the radiology department but also to the broader medical record.

Diagnostic mammography performance and race: outcomes in Black and White women

BACKGROUND

A previous study compared the performance (sensitivity, specificity, positive predictive value, and cancer detection rate) of screening mammography in Black and White women. No study, to the authors' knowledge, has evaluated the difference in the performance of diagnostic mammography between Black and White women.

METHODS

Univariate analysis was used to evaluate differences in characteristics and cancers between Black and White women. Stratified and adjusted logistic regression analyses were used to test the association of Black and White race with performance measures of diagnostic mammography.

RESULTS

The sensitivity of diagnostic mammography was higher (91% vs. 84%) and specificity was lower (86% vs. 90%) among Black women compared with White women. After controlling for age, density, self-reported breast problems, and previous mammography, sensitivity was significantly higher (odds ratio [OR] = 1.82, 95% confidence interval [CI] = 1.22-2.80) and specificity was significantly lower (OR = 0.75, 95% CI = 0.70-0.81) among Black women. The crude cancer detection rate of mammography was higher for Black women (42.6/1000) than for White women (31.0/1000) and Black women had a higher proportion of cancers that were > 2.0 cm (57.4% vs. 46.2%) that were more often poorly differentiated (61.7% vs. 49.3%) and were more often estrogen-receptor and progesterone-receptor negative.

CONCLUSIONS

Black women have lower specificity of diagnostic mammography and, consequently, more unnecessary workups than White women. Black women have higher sensitivity of diagnostic mammography, with cancers that are larger and more advanced than White women. Delay in responding to signs and symptoms would explain the size and later stage. However, more research is needed to understand the biologic differences of breast cancer characteristics between Black and White women.