University of California, San Diego
La Jolla, California, 92093, United States
Location status: Recruiting
Location contact
Breast Research Team
CONTACT
Kay Yeung, MD, PhD
CONTACT
NCT Number: NCT07227233
The goal of this clinical trial is to learn if an artificial intelligence model will be able to select patients with advanced breast cancer who may respond to a second cyclin-dependent kinase 4/6 (CDK4/6) inhibitor after they have progressed on the first CDK4/6 inhibitor. Patients for this study need to have hormone receptor positive (HR+) human epidermal growth factor receptor 2 negative (HER2-) advanced breast cancer.
The main questions the study aims to answer are:
If the artificial intelligence model says that a patient's tumor should respond to the second CDK4/6 inhibitor, and that patient receives the second CDK4/6 inhibitor together with fulvestrant (an endocrine therapy also called Faslodex), will it take longer for the tumor to get worse than if the patient receives another type of therapy? Will the tumor respond better? Will the therapy be safe?
Researchers will compare the combination of a second CDK4/6 inhibitor plus fulvestrant to the therapy chosen by the physician.
Participants will:
Take the assigned therapy based on the way the therapy is usually prescribed. Visit the clinic once every month for checkups, tests, and questionnaires. Keep a diary of the pills they take at home.
Interested in participating?
Request Info18 year and older
All sexes
Interventional
Phase 2
La Jolla, California, 92093, United States
Location status: Recruiting
Breast Research Team
CONTACT
Kay Yeung, MD, PhD
CONTACT
This is a phase II, open-label, randomized controlled single-site study to assess the clinical utility of an artificial intelligence model, called palbo-VNN, to guide treatment selection in patients with hormone receptor positive (HR+) human epidermal growth factor receptor 2 negative (HER2-) advanced (unresectable or metastatic) breast cancer who have progressed after prior treatment with a cyclin-dependent kinase 4/6 (CDK4/6) inhibitor. The investigators hypothesize that: (1) the model will be able to predict who will respond to a second CDK4/6 inhibitors combined with fulvestrant (Faslodex); and (2) that the participants treated with a second CDK4/6 inhibitors plus fulvestrant will have better outcomes (longer progression free survival, higher overall response rate, higher clinical benefit rate, and better quality of life) than the participants treated based on the physician's choice.
Next-generation sequencing of the tumor will be performed using biopsies obtained after the first CDK4/6 inhibitor treatment and within six months of study enrollment. The next-generation sequencing data will be analyzed with the palbo-VNN model. Participants with tumors predicted to respond to a second CDK4/6 inhibitor (CDK4/6i sensitive) will be randomized. Half of the randomized participants will receive a second CDK4/6 inhibitor plus fulvestrant; the other half will receive the treatment of physician's choice, excluding CDK4/6 inhibitors.
After 6 months of therapy, the investigators will evaluate the progression free survival rate of the randomized participants, as well as other measures of efficacy, such as overall response rate, clinical benefit rate, and quality of life. They will also do studies to correlate treatment efficacy with molecular alterations of the tumor. These correlative studies may allow to improve the predictive ability of the palbo-VNN model in the future. The investigators will also evaluate treatment safety.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
A CDK4/6 inhibitor different from the first that the participant had received, plus fulvestrant.
Treatment of physician's choice, excluding CDK4/6 inhibitors.
Time frame: 6 months
Rate of progression free survival at 6 months after randomization.
Contact information is provided by the study sponsor or research team.
Breast Research Team
CONTACT
Kay Yeung, MD, PhD
CONTACT
University of California, San Diego
Other
Artificial Intelligence and Machine Learning-Enhanced Biomarker-dRiven CDK4/6 Inhibitor Rechallenge in HR+ HER2- Advanced Breast Tumors.
Acronym: AIM-BRIGHT
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
Published trials that share one or more normalized conditions with this study.
NCT04816006
Anatomic Stage I Breast Cancer AJCC v8, Anatomic Stage II Breast Cancer AJCC v8
Phoenix, Arizona, United States
View Trial DetailsNCT05625659
Breast Cancer, Breast Diseases
Birmingham, Alabama, United States
View Trial DetailsNCT06954337
Breast Cancer, Breast Diseases
Basking Ridge, New Jersey, United States
View Trial DetailsNCT07340541
Breast Cancer, Breast Diseases
Baltimore, Maryland, United States
View Trial Details