Reactions to uncertainty and the accuracy of diagnostic mammography.

BackgroundReactions to uncertainty in clinical medicine can affect decision making.ObjectiveTo assess the extent to which radiologists' reactions to uncertainty influence diagnostic mammography interpretation.DesignCross-sectional responses to a mailed survey assessed reactions to uncertainty using a well-validated instrument. Responses were linked to radiologists' diagnostic mammography interpretive performance obtained from three regional mammography registries.ParticipantsOne hundred thirty-two radiologists from New Hampshire, Colorado, and Washington.MeasurementMean scores and either standard errors or confidence intervals were used to assess physicians' reactions to uncertainty. Multivariable logistic regression models were fit via generalized estimating equations to assess the impact of uncertainty on diagnostic mammography interpretive performance while adjusting for potential confounders.ResultsWhen examining radiologists' interpretation of additional diagnostic mammograms (those after screening mammograms that detected abnormalities), a 5-point increase in the reactions to uncertainty score was associated with a 17% higher odds of having a positive mammogram given cancer was diagnosed during follow-up (sensitivity), a 6% lower odds of a negative mammogram given no cancer (specificity), a 4% lower odds (not significant) of a cancer diagnosis given a positive mammogram (positive predictive value [PPV]), and a 5% higher odds of having a positive mammogram (abnormal interpretation).ConclusionMammograms interpreted by radiologists who have more discomfort with uncertainty have higher likelihood of being recalled

Comparison of S100A8 and PRAME as biomarkers for distinguishing melanoma from melanocytic naevus: a case–control analysis

BackgroundS100A8 is a melanoma biomarker expressed in the melanoma-associated epidermal keratinocytes, but its diagnostic utility has not been compared with other biomarkers, including PRAME.ObjectivesTo compare the utility of S100A8 and PRAME immunohistochemistry (IHC) in the differential diagnosis of melanoma and naevi in a case-control study.MethodsA previously described cohort of 209 melanomas (case samples) and naevi (control samples) dual-immunostained for S100A8 and PRAME were included. For S100A8, previously reported scores indicating the proportion of tumour-associated epidermis stained (0 = indeterminate; 1 = 0-4%; 2 = 5-25%; 3 = 26-50%; 4 = 51-75%; 5 = > 75%) were utilized. PRAME IHC was reviewed by at least two reviewers and a consensus score assigned, with score indicating the proportion of tumour stained (0 = indeterminate; 1 = 0%; 2 = 1-50%; 3 = > 50%). A positive test was defined as > 50% staining.ResultsThe area under the receiver operating characteristic curves for S100A8 (0.833) and PRAME (0.874) were not significantly different from each other (P = 0.22). The diagnostic sensitivity and specificity were 42.4% [95% confidence interval (CI) 32.6-52.8%] and 98.2% (95% CI 93.6-99.8%) for S100A8, and 79.8% (95% CI 70.5-87.2%) and 87.3% (95% CI 79.6-92.9%) for PRAME, respectively. A combined test requiring both S100A8 and PRAME IHC positivity had a sensitivity of 39.4% (95% CI 29.7-49.7%) and specificity of 99.1% (95% CI 95.0-100.0%).ConclusionsS100A8 and PRAME have utility in the diagnostic workup of melanoma, with S100A8 being more specific and PRAME being more sensitive when using this threshold. Our findings suggest that these two immunohistochemical markers may favourably complement one another to improve the detection of melanoma

National Performance Benchmarks for Modern Screening Digital Mammography: Update from the Breast Cancer Surveillance Consortium

Purpose To establish performance benchmarks for modern screening digital mammography and assess performance trends over time in U.S. community practice. Materials and Methods This HIPAA-compliant, institutional review board-approved study measured the performance of digital screening mammography interpreted by 359 radiologists across 95 facilities in six Breast Cancer Surveillance Consortium (BCSC) registries. The study included 1 682 504 digital screening mammograms performed between 2007 and 2013 in 792 808 women. Performance measures were calculated according to the American College of Radiology Breast Imaging Reporting and Data System, 5th edition, and were compared with published benchmarks by the BCSC, the National Mammography Database, and performance recommendations by expert opinion. Benchmarks were derived from the distribution of performance metrics across radiologists and were presented as 50th (median), 10th, 25th, 75th, and 90th percentiles, with graphic presentations using smoothed curves. Results Mean screening performance measures were as follows: abnormal interpretation rate (AIR), 11.6 (95% confidence interval [CI]: 11.5, 11.6); cancers detected per 1000 screens, or cancer detection rate (CDR), 5.1 (95% CI: 5.0, 5.2); sensitivity, 86.9% (95% CI: 86.3%, 87.6%); specificity, 88.9% (95% CI: 88.8%, 88.9%); false-negative rate per 1000 screens, 0.8 (95% CI: 0.7, 0.8); positive predictive value (PPV) 1, 4.4% (95% CI: 4.3%, 4.5%); PPV2, 25.6% (95% CI: 25.1%, 26.1%); PPV3, 28.6% (95% CI: 28.0%, 29.3%); cancers stage 0 or 1, 76.9%; minimal cancers, 57.7%; and node-negative invasive cancers, 79.4%. Recommended CDRs were achieved by 92.1% of radiologists in community practice, and 97.1% achieved recommended ranges for sensitivity. Only 59.0% of radiologists achieved recommended AIRs, and only 63.0% achieved recommended levels of specificity. Conclusion The majority of radiologists in the BCSC surpass cancer detection recommendations for screening mammography; however, AIRs continue to be higher than the recommended rate for almost half of radiologists interpreting screening mammograms. © RSNA, 2016 Online supplemental material is available for this article

An Assessment of the Quality of Mammography Care at Facilities Treating Medically Vulnerable Populations

Women in medically vulnerable populations, including racial and ethnic minorities, the socioeconomically disadvantaged, and residents of rural areas, experience higher breast cancer mortality than do others. Whether mammography facilities that treat vulnerable women demonstrate lower quality of care than other facilities is unknown

Breast Tumor Prognostic Characteristics and Biennial vs Annual Mammography, Age, and Menopausal Status

Screening mammography intervals remain under debate in the United States

Breast Cancer Characteristics Associated With Digital Versus Film-Screen Mammography for Screen-Detected and Interval Cancers

To determine if pathologic findings of screen-detected and interval cancers differ for digital versus film mammography

Cumulative Risk Distribution for Interval Invasive Second Breast Cancers After Negative Surveillance Mammography.

The aim of the current study was to characterize the risk of interval invasive second breast cancers within 5 years of primary breast cancer treatment. We examined 65,084 surveillance mammograms from 18,366 women with a primary breast cancer diagnosis of unilateral ductal carcinoma in situ or stage I to III invasive breast carcinoma performed from 1996 to 2012 in the Breast Cancer Surveillance Consortium. Interval invasive breast cancer was defined as ipsilateral or contralateral cancer diagnosed within 1 year after a negative surveillance mammogram. Discrete-time survival models—adjusted for all covariates—were used to estimate the probability of interval invasive cancer, given the risk factors for each surveillance round, and aggregated across rounds to estimate the 5-year cumulative probability of interval invasive cancer

Cumulative Probability of False-Positive Recall or Biopsy Recommendation After 10 Years of Screening Mammography: A Cohort Study

False-positive mammography results are common. Biennial screening may decrease the cumulative probability of false-positive results across many years of repeat screening but could also delay cancer diagnosis

Reported Mammographic Density: Film-Screen versus Digital Acquisition

To test the hypothesis that American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) categories for breast density reported by radiologists are lower when digital mammography is used than those reported when film-screen (FS) mammography is used