Feature | Breast Imaging | April 18, 2019 | By Greg Freiherr

How Risk Stratification Might Affect Women’s Health

Various factors should be considered when planning to screen for breast cancer

Fatty tissue and breast density may be considered in the context of many factors that affect the occurrence and detection of breast cancer

Fatty tissue and breast density may be considered in the context of many factors that affect the occurrence and detection of breast cancer. Permission to publish provided by DenseBreast-info.org

When planning a screening program to detect the early signs of breast cancer, age is a major consideration. But it should not be the only one, said Diana Miglioretti, Ph.D., a biostatistics professor at the University of California, Davis.

In an April 5 presentation at the Society for Breast Imaging (SBI)/American College of Radiology (ACR) Breast Imaging Symposium in Hollywood, Fla., Miglioretti noted that several factors can strongly affect the development of breast cancer. If women are to be accurately stratified by risk, these factors should be considered, she said.

One of them is age. The biostatistics professor explained how age can influence the risk of breast cancer (the vast majority of breast cancers occur in women older than age 50, according to the breast cancer surveillance consortium, abbreviated as BCSC) — and what it means for screening with FFDM (full-field digital mammography) and DBT (digital breast mammography).

 

How Individual Women Can Calculate Risk

Much of the risk of developing breast cancer depends on multiple factors, which is why BCSC has come up with a breast cancer risk calculator. Miglioretti highlighted this calculator in her symposium presentation. The free-of-charge calculator is available on the web or as an iPhone-compatible app that can be downloaded. It calculates and compares a woman’s risk of cancer to that of the average woman.

“So if a woman has twice the average risk, she might consider more aggressive screening or start screening early,” Miglioretti said.

The calculator considers a woman’s:

  • Age (the risk of developing breast cancer increases with advancing age, according to the BCSC);
  • race and ethnicity (calibrated by BCSC for non-Hispanic white, non-Hispanic black, Asian/Native Hawaiian/Pacific Islander, Native American/Native Alaskan, and Hispanic women);
  • family history of breast cancer, marked by first-degree relatives — such as mother, sisters and daughters — who have had breast cancer;
  • history of breast biopsy (BCSC noted that risk especially increases if past biopsy specimens showed atypical ductal hyperplasia, a noncancerous condition in which the number of ductal cells increases or these cells look abnormal, or lobular carcinoma in situ, a noninvasive condition characterized by abnormal cells in breast lobules); and
  • breast density, which is determined by the relative amounts of fat, epithelial, and connective tissues that appear differently on mammograms due to X-ray attenuation, according to BCSC.

 

Why Considering Multiple Factors Makes Sense

Miglioretti noted that risk assessment is critically important to coming up with a personalized approach to screening, which she strongly advocates. The biggest benefit from breast cancer screening is early detection, she said, because when breast cancer is detected early, “you have more of a chance to prevent death and morbidity.“

But the chance of physical and psychological harm from screening should be considered. Either or both may result from false-positives, she said, noting that physical harm may come from unneeded chemotherapy or surgery. Psychological harm may occur when a woman thinks she has cancer but doesn’t, Miglioretti said.

The development of a personalized screening approach contrasts sharply with current guidelines, which rely heavily on a single factor, age. At least one guideline recommends that screening begin at age 50; others advise the start of screening much younger — one as early as age 40 (the American Cancer Society Guidelines for the Early Detection of Cancer.)

“But there are women in their 50s who are at lower risk than someone in their 40s,” she said. “Using a risk-based approach would actually identify more women with potential benefit from screening than using just age.”

Current guidelines may seem inconsistent because they recommend that screening start at different ages, Miglioretti said. But all guidelines say that women in their 40s should use personal choice to decide whether screening is right for them, she said: “We should empower women to make these decisions for themselves.”

Women, Miglioretti emphasized, should be encouraged to make their own choices about when to start screening and how aggressively to do so (whether annually or biannually, for example). Their decisions should be based on how they value the benefits versus harms, although some patients, she noted, may want to defer to their physicians.

“And that is fine as well,” she said. “Either way, it is the patient’s choice.”

 

Greg Freiherr is a contributing editor to Imaging Technology News (ITN). Over the past three decades, he has served as business and technology editor for publications in medical imaging, as well as consulted for vendors, professional organizations, academia, and financial institutions.

Related content:

VIDEO: Age, Interval and Other Considerations for Breast Screening

BOOK: Breast Cancer Screening: Making Sense of Complex and Evolving Evidence

 Individual and Combined Effects of Age, Breast Density, and Hormone Replacement Therapy Use on the Accuracy of Screening Mammography

Risk Stratification for Screening Mammography: Benefits and Harms

VIDEO: A Discussion on Proposed FDA Rules for Mammography Reporting

FDA Proposes New Rules for Mammography Reporting and Quality Improvement

Related Content

Some Pregnant Women Are Exposed to Gadolinium in Early Pregnancy
News | Women's Health | August 20, 2019
A small but concerning number of women are exposed to a commonly used magnetic resonance imaging (MRI) contrast agent...
Lunit Receives Korea MFDS Approval for Lunit Insight MMG
News | Artificial Intelligence | August 19, 2019
Lunit has announced Korea Ministry of Food and Drug Safety (MFDS) approval of its artificial intelligence (AI) solution...
Imago Systems Announces Collaboration With Mayo Clinic for Breast Imaging

Image courtesy of Imago Systems

News | Mammography | August 14, 2019
Image visualization company Imago Systems announced it has signed a know-how license with Mayo Clinic. The multi-year...
Artificial Intelligence Could Yield More Accurate Breast Cancer Diagnoses
News | Artificial Intelligence | August 13, 2019
University of California Los Angeles (UCLA) researchers have developed an artificial intelligence (AI) system that...
Lake Medical Imaging Selects Infinitt for Multi-site RIS/PACS
News | PACS | August 09, 2019
Infinitt North America will be implementing Infinitt RIS (radiology information system)/PACS (picture archiving and...
Volpara to Distribute Screenpoint Medical's Transpara AI Solution
News | Breast Imaging | August 02, 2019
Volpara Solutions and ScreenPoint Medical BV signed an agreement under which Volpara will sell ScreenPoint's Transpara...
Ikonopedia Releases Automated Combined Reporting Package at AHRA
News | Mammography Reporting Software | July 26, 2019
Ikonopedia showcased its recently released Automated Combined Reporting package and its entire suite of structured...
Hologic Partners With MagView to Develop Unifi EQUIP Solution
Technology | Mammography Reporting Software | July 25, 2019
Hologic announced a partnership with mammography information solutions provider MagView to develop Unifi EQUIP, an...
Fujifilm Releases Tomosynthesis Biopsy Option for Aspire Cristalle Mammography System
Technology | Breast Biopsy Systems | July 24, 2019
Fujifilm Medical Systems U.S.A. Inc. recently expanded its breast imaging solutions with the launch of its...
IBM collected a dataset of 52,936 images from 13,234 women who underwent at least one mammogram between 2013 and 2017.

IBM collected a dataset of 52,936 images from 13,234 women who underwent at least one mammogram between 2013 and 2017, and who had health records for at least one year prior to the mammogram. The algorithm was trained on 9,611 mammograms. Image courtesy of Radiology.

Feature | Artificial Intelligence | July 19, 2019 | Michal Chorev
Breast cancer is the global leading cause of cancer-related deaths in women, and the most commonly diagnosed cancer...