Periodic Reporting for period 2 - QUALITOP (Monitoring multidimensional aspects of QUAlity of Life after cancer ImmunoTherapy - an Open smart digital Platform for personalized prevention and patient management)
Période du rapport: 2021-07-01 au 2022-12-31
Cancer immunotherapy brought about significant progress in cancer treatment. It resulted in high efficacy in some cancers; e.g. up to 60% objective response rate in melanoma and 80% complete response rate in acute lymphoblastic leukaemia. Nevertheless, two main challenges still impede improving cancer patients’ health status and quality of life (QoL) after immunotherapy initiation: 1) a crucial need for “predictive markers” of occurrence of immunotherapy-related adverse events (IR-AEs) to predict and improve patients’ health status and promote their QoL; and, 2) the lack of knowledge on patients after start of immunotherapy outside randomised controlled trials. To reach these goals, significantly more diversified sources of data are required.
QUALITOP aims at developing a European immunotherapy-specific open Smart Digital Platform and using big data analysis, artificial intelligence, and simulation modelling approaches. This will enable collecting and aggregating efficiently real-world data to monitor health status and QoL of cancer patients given immunotherapy. Through causal inference analyses, QUALITOP will identify the determinants of health status regarding IR-AEs and define patient profiles in a real-world context. For this, heterogeneous data sources (big data), both retrospective and prospective --collected for QUALITOP from clinical centres in four EU countries—will integrate lifestyle, genetic, and psychosocial determinants of QoL. Using machine learning approaches, QUALITOP will provide "real-time" recommendations stemming from patient profiles and feedbacks via the Smart Digital Platform. Furthermore, an increased visibility on patients’ behaviour, a better IR-AEs prediction, and an improvement of care coordination will help analysing through simulation modelling approaches the gain in cost-effectiveness. Guidelines will be issued over the short and long-term.
QUALITOP aims at developing a European immunotherapy-specific open Smart Digital Platform and using big data analysis, artificial intelligence, and simulation modelling approaches. This will enable collecting and aggregating efficiently real-world data to monitor health status and QoL of cancer patients given immunotherapy. Through causal inference analyses, QUALITOP will identify the determinants of health status regarding IR-AEs and define patient profiles in a real-world context. For this, heterogeneous data sources (big data), both retrospective and prospective --collected for QUALITOP from clinical centres in four EU countries—will integrate lifestyle, genetic, and psychosocial determinants of QoL. Using machine learning approaches, QUALITOP will provide "real-time" recommendations stemming from patient profiles and feedbacks via the Smart Digital Platform. Furthermore, an increased visibility on patients’ behaviour, a better IR-AEs prediction, and an improvement of care coordination will help analysing through simulation modelling approaches the gain in cost-effectiveness. Guidelines will be issued over the short and long-term.
The first 18-month period was dedicated to clinical issues (protocol, patients’ information), IT developments (platform architecture, privacy and security) and analytical researches (methodological overview, analyses of prolective historical data). The communication was developed through a website, social media platforms, and a QUALITOP newsletter.
The second 18-month period was dedicated to the inclusion of patients and the collection of clinical data and quality of life questionnaires (QLQ-C30 and EQ-5D). Patients were followed up to monitor possible adverse events and treatment-related toxicities.
Because of the specificity of CART-cell treatment, an adapted protocol was developed to optimize the data collection. Following the IRB approvals, all the centers (France, Spain, Portugal, The Netherlands) were able to begin patient inclusions. A total of 1794 patients have already been included, of which 1118 are historical patients for whom we have clinical data and 676 are prospective patients. As for quality-of-life questionnaires, 292 patients have completed at least one questionnaire. 56 patients are out of the study: 21 due to death and 11 due to progression of the underlying disease, the others are ongoing and will answer the following questionnaires in the coming months. Once the questionnaire response period is over, it is planned to approve a data transfer agreement between centers in order to start the exploitation and analysis of the data. A publication is under writing.
A digital dexterity programme and digital data-centric transformation strategy were developed to enable a digital medical ecosystem to collaborate across organizational boundaries, unlock the flow of health data across borders, and influence the quantity and quality of provided care. The architecture of the Smart Medical Data Processing Platform (SMDPP) was designed as an open-source platform with Web-presence that provides the framework to deliver better quality of care on the basis of trusted and secure sharing and exchange of normalized patient and therapy data collected. Emphasis has been placed on architectural principles to acquire, manage, and processes disparate heterogeneous medical Big Data based on FAIR (Findable, Accessible, Interoperable, Reusable) principles while ensuring security & privacy.
During this first phase, the interactions between the IT teams and the medical partners clarified the semantics of retrospective data and the conditions of acquisition of these data; A conceptual schema of the available data was elaborated. The schema makes it possible to understand the dependencies between the data and thus to express queries more easily to guaranty data quality. Architecture. Architecture of the monitoring system was proposed allowing data collection, quality control and data exploitation while guaranteeing the non-disclosure of sensitive data; In addition, we implemented and tested clustering algorithms on already acquired dataset in order to understand the characteristics of each algorithm and better predict patient trajectories in the future.
Working on historical databases enable the QUALITOP partners to study the adverse events experienced by the patients according to the treatments received in the last 3 months and patients’ comorbidities. Adverse effects and comorbidities during and after treatment are also evaluated. Based on a collaboration with the eQuiPe study research team in the Netherlands (data linked to the Netherlands Cancer Registry (NCR)), and on the French ImmuCare data, some analyses explored the timing and the determinants of IR-AEs. Self-reported components of quality of life differed among patients who received immunotherapy were also explored. Those analyses served as a basis for future exploration of this question when we will analyse the prospective data.
The second 18-month period was dedicated to the inclusion of patients and the collection of clinical data and quality of life questionnaires (QLQ-C30 and EQ-5D). Patients were followed up to monitor possible adverse events and treatment-related toxicities.
Because of the specificity of CART-cell treatment, an adapted protocol was developed to optimize the data collection. Following the IRB approvals, all the centers (France, Spain, Portugal, The Netherlands) were able to begin patient inclusions. A total of 1794 patients have already been included, of which 1118 are historical patients for whom we have clinical data and 676 are prospective patients. As for quality-of-life questionnaires, 292 patients have completed at least one questionnaire. 56 patients are out of the study: 21 due to death and 11 due to progression of the underlying disease, the others are ongoing and will answer the following questionnaires in the coming months. Once the questionnaire response period is over, it is planned to approve a data transfer agreement between centers in order to start the exploitation and analysis of the data. A publication is under writing.
A digital dexterity programme and digital data-centric transformation strategy were developed to enable a digital medical ecosystem to collaborate across organizational boundaries, unlock the flow of health data across borders, and influence the quantity and quality of provided care. The architecture of the Smart Medical Data Processing Platform (SMDPP) was designed as an open-source platform with Web-presence that provides the framework to deliver better quality of care on the basis of trusted and secure sharing and exchange of normalized patient and therapy data collected. Emphasis has been placed on architectural principles to acquire, manage, and processes disparate heterogeneous medical Big Data based on FAIR (Findable, Accessible, Interoperable, Reusable) principles while ensuring security & privacy.
During this first phase, the interactions between the IT teams and the medical partners clarified the semantics of retrospective data and the conditions of acquisition of these data; A conceptual schema of the available data was elaborated. The schema makes it possible to understand the dependencies between the data and thus to express queries more easily to guaranty data quality. Architecture. Architecture of the monitoring system was proposed allowing data collection, quality control and data exploitation while guaranteeing the non-disclosure of sensitive data; In addition, we implemented and tested clustering algorithms on already acquired dataset in order to understand the characteristics of each algorithm and better predict patient trajectories in the future.
Working on historical databases enable the QUALITOP partners to study the adverse events experienced by the patients according to the treatments received in the last 3 months and patients’ comorbidities. Adverse effects and comorbidities during and after treatment are also evaluated. Based on a collaboration with the eQuiPe study research team in the Netherlands (data linked to the Netherlands Cancer Registry (NCR)), and on the French ImmuCare data, some analyses explored the timing and the determinants of IR-AEs. Self-reported components of quality of life differed among patients who received immunotherapy were also explored. Those analyses served as a basis for future exploration of this question when we will analyse the prospective data.
A literature search showed that little information on IR-AEs is reported in randomized controlled trials, owing to short follow-up time, scarcity of events and lack of reported safety outcome data. This reinforces the importance of the objectives of QUALITOP to understand the causal mechanisms between immunotherapy, IR-AEs and later quality of life.
During the second period, the QUALITOP partners will continue on the patients enrollment, smart digital platform implementation especially (medical Interoperability Language, Security, Privacy Mechanisms and Legal Issues) as well as methodological development to address causal inference, heterogeneous data analyses and quantified simulation model which could be used to forecast effects of policies and optimize resource allocation. The next steps will focus on the transfer of data between centers to start data analysis.
QUALITOP will be the first research aiming to provide detailed information on the impact of immunotherapy on QoL (during and after treatment) by including a wide range of medical and psychosocial data and using both qualitative and quantitative data. QUALITOP cohort will be the first European cohort dedicated to the assessment and prediction of QoL during and after immunotherapy.
During the second period, the QUALITOP partners will continue on the patients enrollment, smart digital platform implementation especially (medical Interoperability Language, Security, Privacy Mechanisms and Legal Issues) as well as methodological development to address causal inference, heterogeneous data analyses and quantified simulation model which could be used to forecast effects of policies and optimize resource allocation. The next steps will focus on the transfer of data between centers to start data analysis.
QUALITOP will be the first research aiming to provide detailed information on the impact of immunotherapy on QoL (during and after treatment) by including a wide range of medical and psychosocial data and using both qualitative and quantitative data. QUALITOP cohort will be the first European cohort dedicated to the assessment and prediction of QoL during and after immunotherapy.