Using advanced technology to predict breast cancer recurrence and chemotherapy benefits
Integrating Clinical, Pathologic, and Immune Features to Predict Breast Cancer Recurrence and Chemotherapy Benefit
['FUNDING_CAREER'] · UNIVERSITY OF CHICAGO · NIH-10881949
This study is looking to help doctors better predict if breast cancer might come back and how well chemotherapy will work by using advanced computer techniques to analyze tissue samples, making it easier and more affordable for patients to understand their treatment options.
Quick facts
| Phase | ['FUNDING_CAREER'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | UNIVERSITY OF CHICAGO (nih funded) |
| Locations | 1 site (CHICAGO, UNITED STATES) |
| Trial ID | NIH-10881949 on ClinicalTrials.gov |
What this research studies
This research aims to improve predictions of breast cancer recurrence and the effectiveness of chemotherapy by integrating clinical, pathologic, and immune features. It utilizes deep learning techniques to analyze pathology samples, which are routinely collected during diagnosis, to identify patterns that may indicate a patient's risk of recurrence. The goal is to create a more accessible and cost-effective method for assessing treatment options, particularly for patients who may not have access to expensive gene expression assays. By refining these predictive models, the research seeks to enhance decision-making for breast cancer treatment.
Who could benefit from this research
Good fit: Ideal candidates for this research are women diagnosed with hormone receptor-positive breast cancer who are at risk for recurrence and may benefit from chemotherapy.
Not a fit: Patients with non-hormone receptor-positive breast cancer or those who are not at risk for recurrence may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more accurate predictions of breast cancer recurrence and better-targeted chemotherapy treatments, ultimately improving patient outcomes.
How similar studies have performed: Preliminary work has shown promise in using deep learning for similar predictive purposes, indicating potential for success in this novel approach.
Where this research is happening
CHICAGO, UNITED STATES
- UNIVERSITY OF CHICAGO — CHICAGO, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: HOWARD, FREDERICK MATTHEW — UNIVERSITY OF CHICAGO
- Study coordinator: HOWARD, FREDERICK MATTHEW
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Conditions: American Cancer Society, Breast Cancer, Cancer Cause, Cancer Etiology, Cancer Prognosis