Artificial Intelligence Supporting CAncer Patients Across Europe - the ASCAPE Project
- Conditions
- Breast CancerProstate CancerQuality of LifeSurvivorshipToxicity
- Interventions
- Other: ASCAPE-based follow-up strategy
- Registration Number
- NCT04879563
- Lead Sponsor
- Region Örebro County
- Brief Summary
ASCAPE (Artificial intelligence Supporting CAncer Patients across Europe) is a collaborative research project involving 15 partners from 7 countries, including academic medical centers, SMEs (small and medium-sized enterprises), research centers and universities, aiming to leverage the recent advances in Big Data and AI (Artificial Intelligence) to support cancer patients' Quality of Life (QoL) and health status. Specifically, ASCAPE aims to provide personalized- and AI-based predictions for QoL issues in breast- and prostate cancer patients as well as suggest potential interventions to their physicians.
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 875351.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- ACTIVE_NOT_RECRUITING
- Sex
- All
- Target Recruitment
- 500
Not provided
Not provided
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- SINGLE_GROUP
- Arm && Interventions
Group Intervention Description ASCAPE-based follow-up strategy ASCAPE-based follow-up strategy Follow-up through ASCAPE platform including AI-based predictions for health-related QoL issues and suggestions for personalized interventions.
- Primary Outcome Measures
Name Time Method Patients' experience using ASCAPE-based follow-up At the end of intervention (month 12) Patients' experience to be followed with the help of an AI-based system per se, patients' satisfaction with this type of follow-up, potential barriers and facilitators of using wearables during follow-up, and motivation for following interventions based on AI-based follow-up
- Secondary Outcome Measures
Name Time Method Patients' engagement to ASCAPE-based follow-up Every three months until the end of intervention (12 months) Number of questionnaires submitted per patients; total time that the patients used the wearables
Patients' adherence to AI-based proposed intervention Every three months until the end of intervention (12 months) Physicians' experience in using ASCAPE-based follow-up At the end of intervention (month 12) This outcome includes issues related to trustworthiness, how confident physicians are regarding the reliability of AI-based follow-up, and psychological aspects in using an AI-based platform in clinical practice as perceived substitution crisis and behavioural intention.
Physicians' views and experience regarding ASCAPE-based follow-up in terms of implementation into clinical practice At the end of intervention (month 12) The following aspects will be considered: improvement in patient-doctor relationship; AI-based follow-up's efficiency to capture relevant QoL issues on time; changes in management or referrals made due to AI-based predictions; usefulness of the information provided by AI-based models; acceptability of integrating AI-based follow-up into clinical practice; assessment of the time needed to use AI-based follow-up in clinical practice
Assessment of health-related QoL over time Every three months until the end of intervention (12 months) Physicians' views and experience regarding ASCAPE-based follow-up in terms of interaction At the end of intervention (month 12) This outcome includes issues related to the interaction between the AI-based follow-up platform and physicians as usability, accessibility, and qualitative assessment of the interface.
Trial Locations
- Locations (5)
Department of Oncology, University Hospital of Uppsala
🇸🇪Uppsala, Sweden
CareAcross
🇬🇧London, United Kingdom
Oncology Department, Hospital Clínic de Barcelona
🇪🇸Barcelona, Spain
Department of Oncology, Örebro University Hospital
🇸🇪Örebro, Sweden
Urology Department, Sismanogleio General Hospital
🇬🇷Athens, Greece