About the Mammo OUTPuT tool
The optimal age to initiate breast cancer screening is a source of substantial debate in health care policy, which can lead to uncertainty for healthcare administrators and clinicians seeking to create policies for their organizations.
Part of the current dilemma is that the guidelines from major organizations on breast cancer screening initiation (the age at which to start screening) are conflicting due to the different weight each organization has placed on the evidence from observational studies and clinical trials, and the benefits versus harms of screening:
| Organization | Recommendations |
| American College of Radiology (ACR) | Annual screening starting at age 40 |
| American College of Obstetrics and Gynecology (ACOG) | Annual screening starting at age 40 |
| American Cancer Society (ACS) | Annual screening from ages 45-54 |
| United States Preventive Services Task Force (USPSTF) | Screening before age 50 should be based on the woman’s preferences and individual risk |
The Mammo OUTPuT tool was designed to address this issue. It is a web-based tool that enables policy-makers to make informed decisions about the benefits and harms of earlier breast cancer screening initiation ages within the context of organization/program goals and the population of women they are serving.
What does the tool do?
Mammo OUTPuT is a web-based decision aid intended to provide health care policy-makers with quantitative data on the trade-offs of benefits and harms related to the age of initiation of mammography screening in different groups of women. The data can be used create stratified policies on breast cancer screening initiation age for different populations of women.
The tool is intended to help decision-makers and cancer control planners to:
- View the results of a range of screening strategies applied to different groups of women
- See how screening strategies affect population benefits and harms over a lifetime horizon
- Identify potential public health infrastructure needs (e.g., diagnostic imaging, surgeons for performing biopsies, oncologists to treat cancer) for a given population based on induced services related to different screening initiation ages
- Generate potential research questions and program opportunities based on their populations’ needs and interests.
The results are for populations of women and are not intended for use in individual decision-making.
Example
Using the Mammo OUTPuT tool, you could see how many more deaths could be avoided in a population of women age 40 with extremely dense breasts if they started annual or biennial screening at age 40, compared to waiting to screen until age 50.
You could then change the age to 42, 45, 48, etc. to view the relative benefits and harms of screening at later ages for women with extremely dense breasts.
How does the tool work?
Within the Mammo OUTPuT tool, you can choose among the following criteria to represent different populations of women:
- Screening start age: All ages 40-49 or individual years (40, 41, 42, …, or 49)
- Screening interval: Annual or biennial until age 49
- Mammographic breast density: All densities combined, or almost entirely fatty, scattered fibroglandular density, heterogeneously dense, and extremely dense
For any combination of the above characteristics, you can view the following outcomes per 1000 women:
- Total number of breast cancer diagnoses (incidence)
- Invasive breast cancer diagnoses
- Ductal carcinoma in situ (DCIS) diagnoses
- Breast cancer deaths avoided
- Breast cancer mortality reduction (percent)
- Life years gained
- False positive mammograms
- Benign biopsies
- Overdiagnosis for all breast cancer diagnoses (percent)
- Overdiagnosis for invasive breast cancer diagnoses (percent)
- Overdiagnosis for ductal carcinoma in situ (DCIS) diagnoses (percent)
To compare the scenarios, the tool assumes that current practice includes biennial screening from ages 50 to 74 and thus includes the outcomes expected from screening every other year from ages 50 to 74 (shown in light blue on the graph). The user can then use the tool to view outcomes expected if screening were to start at an age earlier than age 50 (shown in dark blue on the graph).
For example, the user could view how many more deaths could be averted in a population of women age 40 with extremely dense breasts if they started annual screening at age 40, compared to waiting to screen until age 50. The difference in scenarios is then shown in green in a separate graph below. For ease of interpretation, the results are color-coded as follows:
- Scenario 1: results when screening starts in the 40’s
- Scenario 2: results when screening biennially from 50-74
- Difference: the difference between Scenario 1 and 2
A glossary of terms is available within the tool, as well as further details on how to interpret the results.
Video demonstration
The video below provides a demonstration of how to navigate the tool (please note: there is no audio). To get the most out of the tool, the user should start by reading the About the tool, Modeling and methods, Interpretation hints, and Glossary tabs, as shown in the video.
The user can then view different scenarios by choosing options within the tool from the dropdowns on the left. Please note: hovering over the bars of the graphs provide additional information.
You can view the video in full screen by clicking the button with 4 outward-pointing arrows in the lower right-hand corner.
Development of the tool
The MammoOUTPuT tool was developed by researchers and clinicians in the Breast Cancer Working Group of the Cancer Intervention and Surveillance Modeling Network (CISNET).
The data in the tool is based on three established simulation models from CISNET. Three independent modeling teams did this work from the Dana-Farber Cancer Institute, Harvard Medical Center (PI: Sandra Lee, ScD), Erasmus Medical Center (PI: Harry J. de Koning, MD, PhD), and the University of Wisconsin (PIs: Amy Trentham-Deitz, MD, Natasha K Stout, PhD, and Oguzhan Alagoz, PhD).
The development and evaluation of this tool was led by Elizabeth S. Burnside, MD, MPH, Sandra Lee, ScD, Hui Huang, MS, and Jeanne Mandelblatt, MD, MPH. The interactive charts and user interface were designed and implemented by Cornerstone Systems Northwest.
Funding
Financial support of this tool was provided by the National Cancer Institute of the National Institutes of Health under award number U01CA152958 and a contract to Cornerstone supported under NCI grant U01 CA152958. This work was also supported in part by National Institutes of Health grants R01CA165229 and K24CA194251, the University of Wisconsin Carbone Cancer Support Grant P30CA014520, by grants and contracts that support the Breast Cancer Surveillance Consortium (P01CA154292,U54CA163303, HHSN261201100031C), and by the Clinical and Translational Science Award (CTSA) program, through the NIH National Center for Advancing Translational Sciences (NCATS), grant UL1TR000427. The funding agreements ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Please send questions, comments and suggestions to HIPxChange@hip.wisc.edu
Reference
Burnside ES, Lee SJ, Bennette C, Near AM, Alagoz O, Huang H, van den Broek JJ, Kim JY, Ergun MA, van Ravesteyn NT, Stout NK, de Koning HJ, Mandelblatt JS. Using Collaborative Simulation Modeling to Develop a Web-Based Tool to Support Policy-Level Decision Making About Breast Cancer Screening Initiation Age. MDM Policy Pract. 2017 Jul;2(2):2381468317717982.
Use of the Tool
The Mammo OUTPuT tool, available at http://www.hipxchange.org/MammoOUTPuT, is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.