Optimized Multi-modality Machine Learning Approach During Cardio-toxic Chemotherapy to Predict Ar… (NCT02934971) | Clinical Trial Compass
UnknownNot Applicable
Optimized Multi-modality Machine Learning Approach During Cardio-toxic Chemotherapy to Predict Arising Heart Failure
Germany470 participantsStarted 2017-01
Plain-language summary
The present project will develop an automated machine learning approach using multi-modality data (imaging, laboratory, electrocardiography and questionnaire) to increase the understanding and prediction of arising heart failure in patients scheduled for cardio-toxic chemotherapy. This algorithmus will be developed by the technical cooperation partner at Technion, the institut for biomedical engineering in Haifa, Israel.
Who can participate
Age range
18 Years – 100 Years
Sex
FEMALE
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Inclusion criteria
. Patients Patients scheduled for chemotherapy at increased risk of cardiotoxicity (regarding 200 Chemo patients in stage 1 study and 70 Chemo patients in stage 2 study):
. Female aged \> 18 years
. Written informed consent prior to study participation
. The subject is willing and able to follow the procedures outlined in the protocol The department of gynecology at the RWTH University hospital will inform the principal investigator about these patients.
Exclusion criteria
. Valvular stenosis or regurgitation of \>moderate severity
Questions worth asking your doctor
Bring these to your next appointment. They're a starting point for a shared conversation — not a sign you qualify or a recommendation to enrol.
1This study is tracking changes in heart function over a full year using MRI as the gold standard — how many MRI scans would I need to have during that time, and is that realistic given my current treatment schedule?
2Since this trial is focused on predicting heart failure caused by chemotherapy rather than testing a new treatment, what would actually change about my care if the study's machine learning approach flagged a problem with my heart early — would my chemotherapy be adjusted?
3The recruitment status for this trial is listed as 'unknown,' so is this study still actively enrolling patients, and if not, are there similar cardio-oncology monitoring studies I could consider instead?
4Given that this trial is in a non-interventional phase focused on prediction and monitoring, would joining it affect or delay any standard heart-protective treatments I might otherwise receive during chemotherapy?
5How does the type of chemotherapy I'm being given compare to the cardio-toxic regimens being studied here, and does my doctor think my heart-failure risk is significant enough that this level of MRI-based monitoring would be worth discussing?
Generated to help you prepare — always confirm anything about your own eligibility and care with the study team and your doctor.
Questions for the trial coordinator
The trial coordinator is the person who runs the study day to day. These cover the practical side — logistics, costs, and what taking part would actually mean for your life. The study team confirms whether you meet the criteria; these are questions to ask, not a sign you qualify.
1What does taking part actually involve week to week — how many visits, where, and how long does each one take?
2What costs are covered by the study, and what might I have to pay for myself, including travel, parking, or time off work?
3What happens during screening, and what happens if the study team confirms I don't meet the criteria after those tests?
4Who pays for the scans, blood work, and other tests the trial requires — the study, my insurance, or me?
5How will being in the trial affect my regular care, and will my own doctor stay informed and involved?
6Can I leave the trial at any point if I change my mind, and what would happen to my care if I do?
A starting point for the conversation — always confirm anything about your own eligibility, costs, and care with the study team and your doctor.
What they're measuring
1
Change in LVEF from baseline to one year, as determined by MRI as gold standard according to random study group allocation