Utilization of Computer-Aided Detection for Digital Screening Mammography in the United States, 2008 to 2016.

Purpose: Computer-aided detection (CAD) for screening mammography is a software technology designed to improve radiologists' reading performance. Since 2007, multiple Breast Cancer Surveillance Consortium research papers have shown that CAD decreases performance by increasing recalls and decreasing the detection of invasive cancer while increasing the detection of ductal carcinoma in situ. The aim of this study was to test the hypothesis that CAD use by digital mammography facilities would decrease over time.

Four Principles to Consider Before Advising Women on Screening Mammography.

This article reviews four important screening principles applicable to screening mammography in order to facilitate informed choice. The first principle is that screening may help, hurt, or have no effect. In order to reduce mortality and mastectomy rates, screening must reduce the rate of advanced disease, which likely has not happened.

Promoting screening mammography: insight or uptake?

The US Preventive Services Task Force has emphasized individualized decision-making regarding participation in screening mammography for women ages 40 to 49. Positive public opinion regarding screening mammography is understandable given that screening advocates have heavily promoted the slogan "early detection saves lives" while ignoring screening harms. The goal of mammography screening advocates is to increase screening participation or uptake.

What is the point: will screening mammography save my life?

Background: We analyzed the claim "mammography saves lives" by calculating the life-saving absolute benefit of screening mammography in reducing breast cancer mortality in women ages 40 to 65.

Methods: To calculate the absolute benefit, we first estimated the screen-free absolute death risk from breast cancer by adjusting the Surveillance, Epidemiology and End Results Program 15-year cumulative breast cancer mortality to account for the separate effects of screening mammography and improved therapy. We calculated the absolute risk reduction (reduction in absolute death risk), the number needed to screen assuming repeated screening, and the survival percentages without and with screening.

How does age affect baseline screening mammography performance measures? A decision model.

Background: In order to promote consumer-oriented informed medical decision-making regarding screening mammography, we created a decision model to predict the age dependence of the cancer detection rate, the recall rate and the secondary performance measures (positive predictive values, total intervention rate, and positive biopsy fraction) for a baseline mammogram.

Methods: We constructed a decision tree to model the possible outcomes of a baseline screening mammogram in women ages 35 to 65. We compared the single baseline screening mammogram decision with the no screening alternative.