Lazaros Tzelves, Ioannis Varkarakis, Athanasios Anastasiou, Andreas Skolarikos, Ioannis Manolitsis, Antonios Valachis, Serge Autexier, Lucian Itu, Mirjana Ivanovic, Thanos Kosmidis, Konstantinos Perakis, Johannes Rust, Paris Kosmidis

In: Journal of Urology 206 3S e Page 885 American Urological Association Education and Research, Inc. 9/2021.


INTRODUCTION AND OBJECTIVE: Prostate cancer (PCa) is one of the most common neoplasms in Europe, with annual incidence of 336.000. PCa patients frequently encounter health-related quality of life (QOL) issues commonly underestimated.Artificial Intelligence (AI) is used in several healthcare domains, offering the advantage of continuous training on large datasets. The aim of ASCAPE Project is to leverage the advances in Big Data and AI, to support patients with PCa, regarding QOL issues. METHODS: ASCAPE is a collaborative project with 15 partners (Greece, United Kingdom, Sweden, Spain, Germany, Serbia, Romania), taking place in 3 phases. In phase 1, large retrospective datasets will be analyzed to train AI-based models for QOL issues (fatigue, depression, anxiety, incontinence-erectile dysfunction after surgery, hot flushes). During phase 2, a prospective study will be performed, including data collection from validated questionnaires and wearable data for active monitoring of physical activity, sleep pattern and heart rate. Both retrospective and prospective data will be incorporated in an ASCAPE-integrated prototype, which will permit personalized, AI-based predictions and intervention suggestion. In phase 3, evaluation of ASCAPE from patient and physician perspective will be performed, using specific key performance indicators. Eligible patients will have biopsy proven PCa of any stage, who undergo surgery or radiation therapy, with or without hormonal therapy and will be able to use smartwatches to collect data. All patients will participate after signing an informed consent. Follow-up duration will be 12 months after surgery or initiation of radiation therapy, while questionnaires (EORTC-QLQ C30, EORTC- QLQ PR25, Hospital Anxiety and Depression Scale questionnaire, International Index of Erectile Function questionnaire) will be completed every 3 months. Three centers (UK, Sweden, Greece) will recruit patients, while estimated number is 300 patients. RESULTS: Figure CONCLUSIONS: The aim of ASCAPE is to improve QOL of patients with PCa, using AI to detect QOL issues earlier and suggest interventions, based on already successful treatments in patients with similar experiences. Continuous learning and improvement of AI algo- rithms, makes this project very promising for the field of QOL in PCa.


Weitere Links

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz