Periodic Reporting for period 2 - CARDIOCARE (AN INTERDISCIPLINARY APPROACH FOR THE MANAGEMENT OF THE ELDERLY MULTIMORBID PATIENT WITH BREAST CANCER THERAPY INDUCED CARDIAC TOXICITY)
Periodo di rendicontazione: 2023-01-01 al 2024-06-30
Breast cancer is the most diagnosed cancer in Europe, accounting for 13,3% of all new cancer cases in 2020. Female breast cancer is the most frequent cancer reaching 355.000 cases in EU-27 in 2020. 1 in 11 women in EU-27 will develop breast cancer by the age of 74. About half of all new breast cancer patients are diagnosed at the age of 65 and above. Although breast cancer mortality rates have been declining each year in Europe, one of the main causes of non-cancer related death in women with breast cancer over the age of 50 is cardiotoxicity. Cardiotoxicity is the damage caused to the heart due to the cancer therapy complications, reducing life expectancy and Quality of Life significantly. The majority of the newly diagnosed breast cancer patients are older than 65 years of age, adding further complexity to the management and care of this patient population. Currently evidence-based best practices for risk stratification and management of the elderly cancer patients, including older women with breast cancer, are still lacking.
CARDIOCARE is an ambitious 5-year project which aims to rationally change the current state-of-the-art in the management of co-morbid cardiotoxicity in the elderly breast cancer patients. CARDIOCARE provides comprehensive solutions and actionable insights to assist prevention, improved stratification, early detection, and treatment of cardiotoxicity in the elderly breast cancer patients focusing on interventions for preserving the Quality of Life and intrinsic capacity in order to improve healthcare pathways.
To achieve its objectives, the consortium of CARDIOCARE is composed of highly multidisciplinary group of researchers with remarkable track record and complementarity. The CARDIOCARE consortium encompasses partners from 6 clinical centers, 3 private companies (2 SMEs), 1 research institute and 2 universities. Key partner of the project is the European Society of Cardiology, a world leader in the dissemination of best practices in cardiovascular medicine.
CARDIOCARE is an ambitious 5-year project which aims to rationally change the current state-of-the-art in the management of co-morbid cardiotoxicity in the elderly breast cancer patients. CARDIOCARE provides comprehensive solutions and actionable insights to assist prevention, improved stratification, early detection, and treatment of cardiotoxicity in the elderly breast cancer patients focusing on interventions for preserving the Quality of Life and intrinsic capacity in order to improve healthcare pathways.
To achieve its objectives, the consortium of CARDIOCARE is composed of highly multidisciplinary group of researchers with remarkable track record and complementarity. The CARDIOCARE consortium encompasses partners from 6 clinical centers, 3 private companies (2 SMEs), 1 research institute and 2 universities. Key partner of the project is the European Society of Cardiology, a world leader in the dissemination of best practices in cardiovascular medicine.
Smart recommendations have been created for patients and physicians based on psychological constructs identified through psychometric measures via the ePsycHeart App. Patients receive recommendations, like Biofeedback sessions, on their smartphones if their scores exceed clinical thresholds in specific questionnaires.
Data analysis was conducted on retrospective datasets from five clinical centers (BOCOC, IEO, KSBC, NKUA, UOI), involving women aged 55+, diagnosed with breast cancer, with or without cardiovascular risk factors. Two analyses were performed: one adhering to the original cardiotoxicity definition per the retrospective study protocol and another using a new cardiotoxicity definition from the amended prospective study protocol.
The clinical study, closely monitored for challenges, continues collecting samples. The validation of 16S metagenomics sequencing procedures, including storage, DNA extraction, library preparation, and sequencing, was successfully completed.
For developing and validating machine learning risk models, both retrospective and prospective data are being used. Retrospective data collection is complete, with data from 1,587 unique patients (exceeding the 1,560 anticipated in the DoA). Analysis includes non-imaging and imaging data. Measurements from each clinical site were analyzed to correctly identify and assign features in the retrospective database. For imaging data, deep learning segmentation networks were developed for delineating cardiac structures using 2D echocardiography images. Initially, publicly available datasets were used for segmentation models, with two integration strategies identified: feature-level integration and a decision-level approach to strengthen decision support and early diagnosis of cardiotoxicity and QoL declines.
A study protocol was established to refine the cardiotoxicity predictive model and test the efficacy of behavioral and psychological interventions in the CARDIOCARE mobile apps. Developed in collaboration with technical partners, the protocol focuses on ethical data privacy issues. The prospective study is ongoing, with 328 patients enrolled by M36. Data from this study will validate and improve risk models, enhancing diagnosis, prevention, therapy of cardiotoxicity, and improving patients' QoL.
The platform architecture’s initial design was delivered, including a version for data collection, harmonization, storage, processing, and eHealth services while ensuring data protection. The monitoring platform was later extended, and the CARDIOCARE private cloud environment at FORTH expanded to meet increased needs.
Project communication began with the project identity kit (logo, color guide, typeface) at the end of M1. By the end of the first reporting period, the consortium achieved several milestones: launching a website (https://cardiocare-project.eu/(si apre in una nuova finestra)) creating social media channels, posters, brochures, newsletters, press releases, videos, conference presentations, and a journal publication, organizing events for patient associations and healthcare experts, hosting a workshop at the IEEE BHI conference, and establishing synergies with other EU-funded programs. In the second period, more newsletters, flyers (including PILs in English, Swedish, Italian), and a press release were produced. The project also organized a regulatory workshop and uploaded five videos to the CARDIOCARE YouTube channel, covering patient interviews, regulatory workshops, TV presentations, and participation in events like Innohealth Satellite Event 4 and ESC Congress 2023. CARDIOCARE engaged in 11 events to share knowledge with stakeholders and participated in three exhibitions: Expo Zone at ESC Congress 2023, InnoHealth Forum 2023, and Innovent Forum 2024.
Regarding exploitation, a preliminary analysis was conducted, defining the initial exploitable assets of the CARDIOCARE project and identifying key users. A business model canvas detailed key partners, activities, resources, value propositions, customer segments, channels, costs, and revenue streams. In the second reporting period, focus shifted to refining exploitation strategies and plans, aligning them with the project’s progress and results.
Data analysis was conducted on retrospective datasets from five clinical centers (BOCOC, IEO, KSBC, NKUA, UOI), involving women aged 55+, diagnosed with breast cancer, with or without cardiovascular risk factors. Two analyses were performed: one adhering to the original cardiotoxicity definition per the retrospective study protocol and another using a new cardiotoxicity definition from the amended prospective study protocol.
The clinical study, closely monitored for challenges, continues collecting samples. The validation of 16S metagenomics sequencing procedures, including storage, DNA extraction, library preparation, and sequencing, was successfully completed.
For developing and validating machine learning risk models, both retrospective and prospective data are being used. Retrospective data collection is complete, with data from 1,587 unique patients (exceeding the 1,560 anticipated in the DoA). Analysis includes non-imaging and imaging data. Measurements from each clinical site were analyzed to correctly identify and assign features in the retrospective database. For imaging data, deep learning segmentation networks were developed for delineating cardiac structures using 2D echocardiography images. Initially, publicly available datasets were used for segmentation models, with two integration strategies identified: feature-level integration and a decision-level approach to strengthen decision support and early diagnosis of cardiotoxicity and QoL declines.
A study protocol was established to refine the cardiotoxicity predictive model and test the efficacy of behavioral and psychological interventions in the CARDIOCARE mobile apps. Developed in collaboration with technical partners, the protocol focuses on ethical data privacy issues. The prospective study is ongoing, with 328 patients enrolled by M36. Data from this study will validate and improve risk models, enhancing diagnosis, prevention, therapy of cardiotoxicity, and improving patients' QoL.
The platform architecture’s initial design was delivered, including a version for data collection, harmonization, storage, processing, and eHealth services while ensuring data protection. The monitoring platform was later extended, and the CARDIOCARE private cloud environment at FORTH expanded to meet increased needs.
Project communication began with the project identity kit (logo, color guide, typeface) at the end of M1. By the end of the first reporting period, the consortium achieved several milestones: launching a website (https://cardiocare-project.eu/(si apre in una nuova finestra)) creating social media channels, posters, brochures, newsletters, press releases, videos, conference presentations, and a journal publication, organizing events for patient associations and healthcare experts, hosting a workshop at the IEEE BHI conference, and establishing synergies with other EU-funded programs. In the second period, more newsletters, flyers (including PILs in English, Swedish, Italian), and a press release were produced. The project also organized a regulatory workshop and uploaded five videos to the CARDIOCARE YouTube channel, covering patient interviews, regulatory workshops, TV presentations, and participation in events like Innohealth Satellite Event 4 and ESC Congress 2023. CARDIOCARE engaged in 11 events to share knowledge with stakeholders and participated in three exhibitions: Expo Zone at ESC Congress 2023, InnoHealth Forum 2023, and Innovent Forum 2024.
Regarding exploitation, a preliminary analysis was conducted, defining the initial exploitable assets of the CARDIOCARE project and identifying key users. A business model canvas detailed key partners, activities, resources, value propositions, customer segments, channels, costs, and revenue streams. In the second reporting period, focus shifted to refining exploitation strategies and plans, aligning them with the project’s progress and results.
The project will employ an interdisciplinary patient-oriented approach by acquiring, processing and analyzing multidimensional datasets. Data will be obtained retrospectively from the available records of the participating hospitals and a multimodal dataset will be generated through a prospective clinical trial designed and executed as part of the CARDIOCARE project.
During the study, imaging, biochemical and molecular data will be combined with wearable devices and sensors, user application inputs, patient and caregiver questionnaires. Data will be stored, managed and processed using a data management platform while state-of-the-art algorithms will be developed and deployed for delivering a risk prediction model to assist clinical decision making towards better health and care, economic growth and sustainability of health systems.
During the study, imaging, biochemical and molecular data will be combined with wearable devices and sensors, user application inputs, patient and caregiver questionnaires. Data will be stored, managed and processed using a data management platform while state-of-the-art algorithms will be developed and deployed for delivering a risk prediction model to assist clinical decision making towards better health and care, economic growth and sustainability of health systems.