Abstract OT-39-01: Artificial intelligence supporting cancer patients across Europe - the ASCAPE project for breast cancer patients

• Published in: Cancer research (Chicago, Ill.) Vol. 81; no. 4_Supplement; p. OT-39-01
• Main Authors: Valachis, Antonios, Autexier, Serge, Grau, Imma, Itu, Lucian, Jakotevic, Dusan, Kosmidis, Thanos, Muñoz, Montserrat, Perakis, Konstantinos, Rust, Johannes, Savic, Milos, Kosmidis, Paris
• Format: Journal Article
• Language: English
• Published: 15.02.2021
• ISSN: 0008-5472; 1538-7445
• DOI: 10.1158/1538-7445.SABCS20-OT-39-01

Abstract Background Many breast cancer patients experience adverse effects of cancer or treatment, which can considerably decrease quality of life (QoL). The current strategy of supporting breast cancer patients does not meet their needs due to the limited personalized-based approach in rehabilitation plan and the lack of healthcare, financial and other resources. ASCAPE (Artificial intelligence Supporting CAncer Patients across Europe) is a collaborative research project involving 15 partners from 7 countries, including academic medical centers, 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’ QoL and health status. Specifically, ASCAPE aims to provide personalized- and AI-based predictions for QoL issues in breast cancer patients as well as suggest potential interventions to their physicians. Trial design During the first part of the project, large-scale retrospective datasets with breast cancer patients will be analyzed to develop and train AI-based models for specific QoL issues. During the second part of the project, a multicenter prospective longitudinal study is planned. Eligible patients will be followed for one year with validated questionnaires regarding different QoL issues, and wearables that will collect active monitoring data on physical activity, sleep pattern, and heart rate. The collected data will be used to further train and optimize the AI-based models and personalized-based intervention suggestions.Based on the retrospective and prospective data, an ASCAPE-integrated prototype will be developed, enabling personalized- and AI-based predictions and intervention suggestions. This approach will be evaluated at the end of the prospective study regarding patients´ and physicians´ experience as well as health economics. Eligibility criteria Breast cancer patients planned for curative treatment with surgery with or without oncological therapy or breast cancer patients at least 1 year post-treatment (except endocrine therapy) will be eligible for the prospective study. Specific aims 1.To develop and optimize AI-based predictions for QoL issues in breast cancer patients as well as potential intervention suggestions.2.To evaluate the AI-based follow-up approach for breast cancer survivors in terms of patients´ experience, physicians´ experience, and health economics. Statistical methods For discrete QoL outcome variables, ASCAPE will examine the efficiency of classification-based machine learning models trained using decision tree learning algorithms, nearest-neighbors based algorithms, probabilistic learning algorithms, support vector machines and (deep) neural networks. Regressive counterparts of aforementioned methods will be analyzed for numeric QoL outcome variables including also regression specific methods (e.g., ridge regression, lasso regression and elastic net regression). The accuracy of trained models will be estimated relying on standard machine learning validation procedures such as the K-fold cross-validation and leave-one-out cross-validation. The ASCAPE platform will utilize state-of-the-art explainability techniques to make the machine learning models’ predictions transparent and comprehensible for the patient and the physician.Present accrual and target accrual Four retrospective datasets will be used for the first part of the project including approximately 18,000 breast cancer patients. For the prospective study, it is planned to be included about 30 patients monthly during a period of 12 months. Contact information for people with a specific interest in the trial https://ascape-project.eu/artificial-intelligence-supporting-cancer-patients-across-europe Citation Format: Antonios Valachis, Serge Autexier, Imma Grau, Lucian Itu, Dusan Jakotevic, Thanos Kosmidis, Montserrat Muñoz, Konstantinos Perakis, Johannes Rust, Milos Savic, Paris Kosmidis. Artificial intelligence supporting cancer patients across Europe - the ASCAPE project for breast cancer patients [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr OT-39-01.