Periodic Reporting for period 3 - REBECCA (REsearch on BrEast Cancer induced chronic conditions supported by Causal Analysis of multi-source data)
Reporting period: 2024-04-01 to 2025-09-30
Patients who complete treatment for cancer often live for many years with complex chronic conditions, such as cancer-related fatigue, pain, bone loss and anxiety. These problems can affect their quality of life, their functional and emotional status, and subsequently their ability to return to work or social activities. However, these problems are not easily captured during hospital visits or through standardised questionnaires. At the same time, large amounts of “real-world data” (RWD) are constantly generated in hospital systems and through smartphones, wearables and online activity. These data have the potential to provide in-depth understanding of the patients’ status, especially between visits to the doctor, but they are rarely used in routine care or for research purposes.
REBECCA has demonstrated that RWD can be collected and analysed at scale to provide improved care pathways and complementary information for clinical studies. The project combined data from electronic health records with continuous monitoring from wearables, smartphones and web browsers. During the project, REBECCA (i) built a secure digital platform for 360° monitoring of patients’ daily life, (ii) developed new “digital biomarkers” that reflect functional, emotional and quality-of-life trajectories, (iii) applied advanced, explainable causal modelling to understand the influence of treatments and complex chronic conditions on the quality of life, and (iv) evaluated whether the REBECCA-assisted patient care could improve patient-reported outcomes, compared to standard care, in real clinical studies in Sweden, Norway and Spain.
The project leaves behind a mature digital platform, new methods and indicators, evidence from six clinical studies, and a sustainability and exploitation strategy that together will support wider adoption of RWD in breast cancer care, other forms of cancer, and the management of complex chronic conditions in general.
REBECCA has demonstrated that RWD can be collected and analysed at scale to provide improved care pathways and complementary information for clinical studies. The project combined data from electronic health records with continuous monitoring from wearables, smartphones and web browsers. During the project, REBECCA (i) built a secure digital platform for 360° monitoring of patients’ daily life, (ii) developed new “digital biomarkers” that reflect functional, emotional and quality-of-life trajectories, (iii) applied advanced, explainable causal modelling to understand the influence of treatments and complex chronic conditions on the quality of life, and (iv) evaluated whether the REBECCA-assisted patient care could improve patient-reported outcomes, compared to standard care, in real clinical studies in Sweden, Norway and Spain.
The project leaves behind a mature digital platform, new methods and indicators, evidence from six clinical studies, and a sustainability and exploitation strategy that together will support wider adoption of RWD in breast cancer care, other forms of cancer, and the management of complex chronic conditions in general.
Over its duration, the project designed, developed and deployed the REBECCA platform, an integrated infrastructure for collecting and analysing real-world data. The platform includes a patient mobile app (linked to commercial wearables), a companion app for caregivers, a web browser plug-in to capture online behaviour, and a clinical dashboard that allows researchers and health professionals to visualise patients’ trajectories over time. The final version of the platform was deployed in three countries and used in six prospective clinical studies involving breast cancer survivors and, in one study, prostate cancer patients.
The project enriched RWD with behavioural, lifestyle and physiological indicators. These cover mobility patterns, physical activity and heart rate, sleep, and aspects of emotional well-being inferred from patients’ online behaviours. REBECCA developed new “digital biomarkers” and data-driven models that summarise functional and emotional status. An Early Warning System was also implemented to flag abrupt changes in behaviour or adherence that may require attention.
To move beyond simple correlations, REBECCA developed and tested a full causal analysis framework for RWD. At the heart of this framework, Directed Acyclic Graphs capture the complex associations between treatments, behaviours, patient variables and patient-reported outcomes. A federated analysis library was developed to enable cross-country studies without sharing sensitive individual-level data.
On the clinical side, REBECCA successfully ran six studies in Sweden, Norway and Spain, ranging from observational studies to feasibility and intervention trials. These studies showed that continuous digital monitoring is feasible and acceptable to cancer patients, survivors and health care professionals. In one of the intervention trials, conducted in Spain, the REBECCA-assisted consultations were associated with statistically significant improvements in emotional and social functioning. Another intervention study in Norway found more modest, non-significant effects on physical functioning but still provided important insights. To support the delivery of REBECCA-assisted interventions, an “Advisory Guide for Health Care Professionals” was developed that links lifestyle advice to REBECCA measurements.
REBECCA placed strong emphasis on data protection, ethics and FAIR (Findable, Accessible, Interoperable, Reusable) data principles. The Data Management Plan and Data Protection Impact Assessment were kept up to date in line with recommendations from independent ethics advisors, and a public Zenodo community was created to host open deliverables, scientific publications and dataset metadata.
A comprehensive cost–benefit analysis using data from one of the intervention studies in Norway quantified the economic value of the REBECCA approach, indicating a positive cost–benefit ratio and suggesting that the intervention can become cost-effective after roughly two years in the examined scenario. This provides an important input for decision-makers considering reimbursement and wider deployment of similar solutions.
On the exploitation front, the consortium developed 14 individual exploitation plans for specific tools and services, 12 collaborative plans involving several partners, and a joint exploitation plan for the REBECCA platform, with a total of 28 exploitable assets identified. Dissemination activities were extensive, with numerous scientific and non-scientific publications, presentations at conferences and events, multiple newsletters and online campaigns, as well as engagement and collaboration with other EU-funded projects to align approaches and maximise impact.
The project enriched RWD with behavioural, lifestyle and physiological indicators. These cover mobility patterns, physical activity and heart rate, sleep, and aspects of emotional well-being inferred from patients’ online behaviours. REBECCA developed new “digital biomarkers” and data-driven models that summarise functional and emotional status. An Early Warning System was also implemented to flag abrupt changes in behaviour or adherence that may require attention.
To move beyond simple correlations, REBECCA developed and tested a full causal analysis framework for RWD. At the heart of this framework, Directed Acyclic Graphs capture the complex associations between treatments, behaviours, patient variables and patient-reported outcomes. A federated analysis library was developed to enable cross-country studies without sharing sensitive individual-level data.
On the clinical side, REBECCA successfully ran six studies in Sweden, Norway and Spain, ranging from observational studies to feasibility and intervention trials. These studies showed that continuous digital monitoring is feasible and acceptable to cancer patients, survivors and health care professionals. In one of the intervention trials, conducted in Spain, the REBECCA-assisted consultations were associated with statistically significant improvements in emotional and social functioning. Another intervention study in Norway found more modest, non-significant effects on physical functioning but still provided important insights. To support the delivery of REBECCA-assisted interventions, an “Advisory Guide for Health Care Professionals” was developed that links lifestyle advice to REBECCA measurements.
REBECCA placed strong emphasis on data protection, ethics and FAIR (Findable, Accessible, Interoperable, Reusable) data principles. The Data Management Plan and Data Protection Impact Assessment were kept up to date in line with recommendations from independent ethics advisors, and a public Zenodo community was created to host open deliverables, scientific publications and dataset metadata.
A comprehensive cost–benefit analysis using data from one of the intervention studies in Norway quantified the economic value of the REBECCA approach, indicating a positive cost–benefit ratio and suggesting that the intervention can become cost-effective after roughly two years in the examined scenario. This provides an important input for decision-makers considering reimbursement and wider deployment of similar solutions.
On the exploitation front, the consortium developed 14 individual exploitation plans for specific tools and services, 12 collaborative plans involving several partners, and a joint exploitation plan for the REBECCA platform, with a total of 28 exploitable assets identified. Dissemination activities were extensive, with numerous scientific and non-scientific publications, presentations at conferences and events, multiple newsletters and online campaigns, as well as engagement and collaboration with other EU-funded projects to align approaches and maximise impact.
REBECCA has advanced the state of the art in several ways. Overall, it showed that the REBECCA platform can be integrated into existing clinical workflows across multiple hospitals and countries to advance patient management through monitoring via wearables, smartphones, and traditional electronic health records, and that such systems can be used for in-depth research into the complex chronic conditions that many patients suffer from.
To achieve this, the project developed new, interpretable digital biomarkers and indices that translate RWD streams into information that can support clinical decisions and patient self-management. Furthermore, the developed causal modelling framework contributes to more reliable use of RWD for understanding cause-and-effect relationships in breast cancer.
The expected impact of these results is both clinical and societal. For patients, better monitoring and understanding of life after cancer treatment can translate into more timely support, more personalised lifestyle advice, and ultimately better quality of life and participation in work and social life. For health systems, tools like REBECCA can help target resources more effectively, support earlier interventions, and potentially reduce costs related to long-term comorbidities and sick leave. For researchers, the platform and analysis methods developed in REBECCA offer a blueprint for future studies on other cancers and chronic diseases that take advantage of RWD.
To achieve this, the project developed new, interpretable digital biomarkers and indices that translate RWD streams into information that can support clinical decisions and patient self-management. Furthermore, the developed causal modelling framework contributes to more reliable use of RWD for understanding cause-and-effect relationships in breast cancer.
The expected impact of these results is both clinical and societal. For patients, better monitoring and understanding of life after cancer treatment can translate into more timely support, more personalised lifestyle advice, and ultimately better quality of life and participation in work and social life. For health systems, tools like REBECCA can help target resources more effectively, support earlier interventions, and potentially reduce costs related to long-term comorbidities and sick leave. For researchers, the platform and analysis methods developed in REBECCA offer a blueprint for future studies on other cancers and chronic diseases that take advantage of RWD.