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Jenciūtė G, Kasputytė G, Bunevičienė I, Korobeinikova E, Vaitiekus D, Inčiūra A, Jaruševičius L, Bunevičius R, Krikštolaitis R, Krilavičius T, Juozaitytė E, Bunevičius A
Digital Phenotyping for Monitoring and Disease Trajectory Prediction of Patients With Cancer: Protocol for a Prospective Observational Cohort Study
Digital Phenotyping for Monitoring and Disease Trajectory Prediction of Patients with Cancer: a Protocol for the Observational Study
Gabrielė Jenciūtė;
Gabrielė Kasputytė;
Inesa Bunevičienė;
Erika Korobeinikova;
Domas Vaitiekus;
Arturas Inčiūra;
Laimonas Jaruševičius;
Romas Bunevičius;
Ričardas Krikštolaitis;
Tomas Krilavičius;
Elona Juozaitytė;
Adomas Bunevičius
ABSTRACT
Background:
Timely recognition of cancer progression and treatment complications is important for treatment guidance. Digital phenotyping is a promising method for precise and remote monitoring of patients in their natural environments using passively generated data from sensors of personal wearable devices.
Objective:
To evaluate whether passively generated data from smartphone sensors is feasible for remote monitoring of cancer patients to predict their disease trajectories and patient-centered health outcomes.
Methods:
We will recruit 200 patients undergoing treatment for cancer. Patients will be followed for six months. Passively generated data by sensors of personal smartphone devices will be continuously collected using the developed LAIMA smartphone application. Every two weeks patients will be asked to complete questionnaires pertaining to quality of life via smartphone application. Two visits will take place at months 1-3 and 3-6. We will examine the association between digital, clinical, and patient-reported health outcomes aiming to develop prediction models of clinically meaningful outcomes.
Results:
The study results will be published in peer-reviewed journals.
Conclusions:
The study will provide in-depth insight into temporally and spatially precise trajectories of cancer patients that will provide with novel digital health approach and will inform design of future interventional clinical trials in oncology.
Citation
Please cite as:
Jenciūtė G, Kasputytė G, Bunevičienė I, Korobeinikova E, Vaitiekus D, Inčiūra A, Jaruševičius L, Bunevičius R, Krikštolaitis R, Krilavičius T, Juozaitytė E, Bunevičius A
Digital Phenotyping for Monitoring and Disease Trajectory Prediction of Patients With Cancer: Protocol for a Prospective Observational Cohort Study