This clinical trial focuses on testing the efficacy of different digital interventions to promote re-engagement in cancer-related long-term follow-up care for adolescent and young adult (AYA) survivors of childhood cancer.
The PREDICT 3 study will build on previous research in over 2,000 individuals to further refine machine learning models that predict individual responses to foods, with the aim of advancing precision nutrition science and individualized dietary advice. The study incorporates both standardized and controlled dietary intervention, for the purpose of testing postprandial responses to specific mixed meals, in addition to a free-living period with a dietary record for measuring responses to a large variety of meals consumed in a realistic context, where the role of external factors (e.g. exercise, sleep, time of day) on postprandial responses may be determined. For the first time this PREDICT study is built on top of a commercial product which will allow access to a much larger group of participants who are already collecting large amounts of data through digital and biochemical devices that can contribute to science.
Personalized Responses to Dietary Composition Trial 3
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
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Sponsor: Zoe Global Limited
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.