We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us

Download Mobile App




New Model Predicts 10 Year Breast Cancer Risk

By HospiMedica International staff writers
Posted on 05 Sep 2023
Print article
Image: The model predicts a woman`s likelihood of developing and dying of breast cancer within a decade (Photo courtesy of Freepik)
Image: The model predicts a woman`s likelihood of developing and dying of breast cancer within a decade (Photo courtesy of Freepik)

Breast cancer screening is a vital tool against the deadly disease, yet it faces its share of challenges. Although it reduces breast cancer-related deaths, it also has the potential to detect non-harmful tumors (overdiagnosis), leading to unnecessary treatments. This not only adversely affects some women but also drives up healthcare costs unnecessarily. 'Risk-based screening' is a strategy aimed at customizing screening approaches based on an individual's risk profile, aiming to maximize benefits and minimize drawbacks. Tailoring screening programs based on individual risks was recently identified as a way to refine screening strategies. Presently, most risk-based breast screening models estimate a woman's risk of being diagnosed with breast cancer. However, not all breast cancers are fatal, and the risk of diagnosis doesn't always align with the risk of death post-diagnosis. Now, researchers have devised a new model that accurately predicts a woman's likelihood of both developing and then succumbing to breast cancer within a decade.

The new model developed by a team of researchers at University of Oxford (Oxford, UK) predicts a woman's 10-year combined risk of breast cancer development and subsequent mortality. The aim is to identify women at the highest risk of deadly cancers in order to enhance the effectiveness of screening programs. Such high-risk individuals might be encouraged to initiate screening earlier, receive more frequent screenings, or undergo different types of imaging. This personalized strategy not only has the potential to reduce breast cancer fatalities but also avoid unnecessary screening for women with lower risk. Women with an elevated risk of deadly cancer could also be considered for preventive treatments against the development of breast cancer.

The research team explored four distinct modeling techniques to predict breast cancer mortality risk. Two followed conventional statistical methodologies, while the other two harnessed machine learning, a branch of artificial intelligence. All models incorporated identical data types, including age, weight, smoking history, family history of breast cancer, and hormone therapy (HRT) usage. The models underwent evaluation for their overall predictive accuracy, spanning various women's groups with diverse characteristics such as different age brackets and ethnic backgrounds. An approach called 'internal-external cross-validation' was employed. This method involves dividing the dataset into structurally distinct segments, based on factors like region and time frame, to assess the model's adaptability across different scenarios. The outcomes revealed that a statistical model constructed using 'competing risks regression' outperformed the rest. This model demonstrated the highest accuracy in predicting which women would develop and face breast cancer mortality within a 10-year span. The machine learning models displayed comparatively lower accuracy, particularly for diverse ethnic women's groups.

“This is an important new study which potentially offers a new approach to screening. Risk-based strategies could offer a better balance of benefits and harms in breast cancer screening, enabling more personalized information for women to help improve decision making,” said University of Oxford Professor Julia Hippisley-Cox. “Risk based approaches can also help make more efficient use of health service resources by targeting interventions to those most likely to benefit.”

Related Links:
University of Oxford 

Gold Member
POC Blood Gas Analyzer
Stat Profile Prime Plus
Gold Member
STI Test
Vivalytic Sexually Transmitted Infection (STI) Array
Silver Member
Wireless Mobile ECG Recorder
NR-1207-3/NR-1207-E
New
Intraventricular Neuroendosopic System
MINOP

Print article
Detecto

Channels

Critical Care

view channel
Image: Vascular flow modeling exemplar; intracranial aneurysm flow, treatment and thrombosis (Photo courtesy of University of Leeds)

Faster, More Accurate Blood Flow Simulation to Revolutionize Treatment of Vascular Diseases

The field of vascular flow modeling is vital for understanding and treating vascular diseases, but traditionally, these methods require extensive labor and computation. Now, researchers have made groundbreaking... Read more

Surgical Techniques

view channel
Image: The prototype pacemaker is made of a specially engineered membrane (Photo courtesy of University of Chicago)

Ultra-Thin, Light-Controlled Pacemaker Regulates Heartbeats

Millions of individuals depend on pacemakers, small yet vital devices that help maintain a regular heartbeat by regulating the heart's electrical impulses. To minimize complications, there is growing interest... Read more

Patient Care

view channel
Image: The newly-launched solution can transform operating room scheduling and boost utilization rates (Photo courtesy of Fujitsu)

Surgical Capacity Optimization Solution Helps Hospitals Boost OR Utilization

An innovative solution has the capability to transform surgical capacity utilization by targeting the root cause of surgical block time inefficiencies. Fujitsu Limited’s (Tokyo, Japan) Surgical Capacity... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The new eye-safe laser technology can diagnose traumatic brain injury (Photo courtesy of 123RF)

Novel Diagnostic Hand-Held Device Detects Known Biomarkers for Traumatic Brain Injury

The growing need for prompt and efficient diagnosis of traumatic brain injury (TBI), a major cause of mortality globally, has spurred the development of innovative diagnostic technologies.... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.