D1.10 - Study 2 Initiation Package

1 A new, interdisciplinary, multi-stakeholder European network to improve healthcare services, research and outcomes for Adolescents and Young Adults with cancer. STRONG-AYA – No. 101057482 – D1.10 Deliverable Report WP1– Development of a Core Outcome Set (COS) for AYAs with cancer and data collection D1.10 Study 2 Initiation Package Due date of deliverable: 31/03/2024 Actual submission date: 31/03/2024 Project: STRONG-AYA Lead Contributor Olga Husson (NKI) Email [email protected] Other Contributors Winette van der Graaf; Renske Fles; Simone Hanebaum; Silvie Janssen Emails w.vd.gr[email protected]; [email protected]; [email protected]; [email protected] Due date 31 03 2024 Delivery date 30 03 2024 Deliverable type R Dissemination level PU Description of Work Version Date V1.0 30/03/2024 STRONG-AYA – No. 101057482 – D1.10 Description: Study 2 initiation package (before enrolment of the first study participant) including: -Registration number of the clinical study in a registry meeting WHO Registry criteria -Final version of study protocol as approved by the regulator(s) / ethics committee(s) -Regulatory and ethics (if applicable, institutional) approvals required for the enrolment of the first study participant Publishable summary (max ½ page) This report provides an overview of the ethics approval for the data collection phase of STRONG AYA. The attached documents include the study protocol filed with the Institutional Review Board at the Netherlands Cancer Institute – Antoni van Leeuwenhoek Hospital. STRONG-AYA – No. 101057482 – D1.10 1 Table of Contents ! PUBLISHABLE SUMMARY (MAX ½ PAGE) ................................................................................................................... 3 1 TABLE OF CONTENTS ........................................................................................................................................ 4 2 DEFINITIONS ..................................................................................................................................................... 5 3 ABBREVIATIONS ............................................................................................................................................... 6 4 INTRODUCTION ................................................................................................................................................ 7 PROJECT BACKGROUND ............................................................................................................................................ 7 5 STUDY 2 INITIATION PACKAGE .......................................................................................................................... 9 6 RESULTS ......................................................................................................................................................... 10 7 REPOSITORY FOR PRIMARY DATA (ANNEX) ..................................................................................................... 11 STRONG-AYA – No. 101057482 – D1.10 2 Definitions STRONG AYA consortium members are referred to as following within this text: 1. NKI-AVL – Stichting het Nederlands Kanker Instituut – Antoni van Leeuwenhoek Ziekenhuis (NL) 2. YCE – Youth Cancer Europe (RO) 3. INT – Fondazione IRCCS Instituto Nazionale dei Tumori (IT) 4. FFUND – FFUND BV (NL) 5. CLB – Centre de Lutte Contre le Cancer Leon Berard (FR) 6. ECO – European Cancer Organisation (BE) 7. UNIMAAS – Universiteit Maastricht (NL) 8. IKNL – Stichting Integraal Kankercentrum Nederland (NL) 9. EORTC – European Organisation for Research and Treatment of Cancer AISBL (BE) 10. IGR – Institut Gustave Roussy (FR) 11. MSCNRIO – Narodowy Instytut Onkologii im. Marii Sklodowskiej-Curie – Panstwowy Instytut Badawczy (Marie Sklodowska-Curie National Research Institute of Oncology) (PL) 12. UOM – University of Manchester (UK) 13. UOL – University of Leeds (UK) 14. LTHT – Leeds Teaching Hospitals National Health Service Trust (UL) 15. SOUTHAMPTON – University of Southampton (UK) • Grant Agreement (including its annexes and amendments): the agreement signed between the beneficiaries of the HORIZON Research and Innovations Actions (hereafter referred to as Horizon) and the European Health and Digital Executive Agency (hereafter referred to as HADEA) for the undertaking of the STRONG AYA project (Grant Agreement no. 101057482). • Beneficiary: Signatories of the Grant Agreement • Associated Partner: Entities which participate in the action but without the right to charge costs or claim contributions. • Project: the sum of all activities carried out in the framework of the Grant Agreement. • Consortium: the STRONG AYA consortium, including all the aforementioned partners. • Consortium Agreement: The agreement made between STRONG AYA members for the implementation and execution of the action outlined in the Grant Agreement. The agreement shall not affect the parties’ obligations to HADEA on behalf of the European Union, and/or to one another arising from the Grant Agreement. STRONG-AYA – No. 101057482 – D1.10 3 Abbreviations Acronym/Abbreviation Meaning HCP Health Care Provider PRO Patient Reported Outcome PROM Patient Reported Outcome Measure COS Core Outcome Set WP Work Package WPL Work Package Lead(s) WP1 Work Package 1 (Development Core Outcome Set AYA with cancer & data collection) WP2 Work Package 2 (Governance, Data Security and Ethics) WP3 Work Package 3 (Infrastructure and Interoperability) WP4 Work Package 4 (Operation of STRONG AYA ecosystems, stakeholder and patient involvement, dissemination, exploitation, communication) WP5 Work Package 5 (Scientific coordination and project management) KPI Key Performance Indicator OA Open Access PAB Patient Advisory Board EC European Commission HADEA European Health and Digital Executive Agency SC Steering Committee MT Management Team STRONG-AYA – No. 101057482 – D1.10 4 Introduction Project background Cancer at adolescent and young adult (AYA) age is rare, although 4-6 times more frequent than paediatric cancer (i.e. prepubescent period). However, this rarity does not reflect the significant personal and societal costs of cancer in this population, as reflected in the potential years of life lost or saved, the decreased productivity and quality-of-life due to the impact of the disease during formative years, and the long-term complications or disabilities 1 . AYAs with cancer form a unique group; they face age-specific issues (e.g. Infertility, unemployment, financial problems) and decreased quality of life due to cancer and its treatment. Unlike dedicated healthcare and trials for paediatric cancer patients, AYA-specific healthcare services are scarce and vary across Europe. AYAs who are at the core of society and economy need access to ageappropriate and high-quality healthcare. Defining AYAs with cancer as 15 to 39 years at initial cancer diagnosis 2 , their annual cancer incidence is 42.2/100.000, with 156.431 cases in Europe and 1.231.007 cases worldwide reported in 2018 (together 6.8% of all cancers) 3 . Population-based data from 27 European countries supports that AYAs have lower survival than children but higher than adults affected by cancer. Advances in cancer treatment have led to increased survival rates for AYAs with cancer, improving by 82% for all cancers between 1990 and 2007 4 . However, survival improvement in AYA is more challenging than for children and older cancer survivors, which might be due to the fact that AYA have the highest absolute excess risk of second primary malignant neoplasms 5 . AYA face some distinct challenges given that they do not belong to neither paediatric nor adult oncology groups. Characteristic features of this population group include unique spectrum of cancer types, different tumour biology, unique complex psychological needs, distinct late sequelae, including impaired fertility, and palliative care. These traits imply that clinical management, treatment, diagnosis, psychological support will need to be designed and developed for AYA’s specific needs. For example, AYAs diagnosed with breast and prostate carcinomas have worse survival than older patients because of the biological differences between them, highlighting the need to target screening methodologies, treatment and policies to their needs 6 . AYAs with cancer also face significant psychological challenges, including substance abuse, mental health issues, suicidal ideations and increased emotional burden from cancer and cancer-related morbidity. Finally, tailoring cancer care to AYA’s needs is difficult and due to many different complex factors including the low rate of participation by AYAs in clinical trials and cancer research 7 . Despite the increasing awareness and a growing body of the scientific literature, these unique issues remain to be fully recognised and addressed by the European health systems and AYAs with cancer are frequently underserved. In part, this may have resulted from the traditional dichotomy between the integrated paediatric (“patient/family-centred”) care services versus dispersed (“diseasecentered”) adult oncology 1 Stoneham SJ. AYA survivorship: The next challenge. Cancer 2020; 126: 2116-2119. 2 Adolescent and Young Adult Oncology Review Group. Closing the gap: Research and Care Imperatives for Adolescents and Young Adults with Cancer. National Institute of Health, National Cancer Institute, and Livestrong Young Ault Alliance: Bethesda, MD, USA, 2006. 3 Trama A, Botta L, Steliarova-Foucher E. Cancer Burden in Adolescents and Young Adults: A Review of Epidemiological Evidence. Cancer J 2018; 24: 256-266 4 Trama A, Botta L, Foschi R et al. Survival of European adolescents and young adults diagnosed with cancer in 2000-07: population-based data from EUROCARE5. Lancet Oncol 2016; 17: 896-906. 5 Keegan THM, Bleyer A, Rosenberg AS et al. Second Primary Malignant Neoplasms and Survival in Adolescent and Young Adult Cancer Survivors. JAMA Oncol 2017; 3: 1554-1557. 6 Stark D, Bielack S, Brugieres L et al. Teenagers and young adults with cancer in Europe: from national programmes to a European integrated coordinated project. European Journal of Cancer Care, 25(3), 419–427. 7 Hayashi RJ. Adolescent and young adult cancer survivorship: The new frontier for investigation. Cancer 2019; 125: 1976-1978. STRONG-AYA – No. 101057482 – D1.10 services 8 , 9 , 10 . Up to half of AYAs with cancer report unmet informational and service needs, impacting their direct (survival rates) and indirect (long term effects and mental health) recovery to participate in society 11 . Furthermore, aligned with this barrier is the low rate of health care utilisation by AYAs, especially primary care, given their challenges to sustain health insurance coverage 12 . According to a survey conducted through the networks of the AYA Working Group of the European Society for Medical Oncology (ESMO) and the European Society for Paediatric Oncology (SIOP Europe), 67% of practitioners do not have access to specialised centres for AYA with cancer, 67% had no access to a specialist cancer service for late effects management and 38% had no access to fertility specialists. Under-provision and inequality of AYA cancer care is common across Europe and especially in the Eastern and Southern-East. Furthermore, the Working Group also reported an absence of outcome measures for monitoring and evaluating AYA cancer care programs and control 13 . Among the recommended future steps, it has been identified that one of the most important contributions to AYA research would be to pool data (e.g. patient-reported outcomes, clinical and treatment data) across institutions and countries and create large cohorts for researchers to Address the burden of cancer in AYA 14 . There is a lack of data standardization, data interoperability and (prospective) collection of outcomes of relevance for AYAs with cancer. The STRONG-AYA project aims to tackle the underrepresentation of AYA’s experiences and outcomes when navigating the healthcare system and in clinical care by developing national infrastructures for outcome data management and clinical decision-making within a pan-European ecosystem and establishing communication feedback for AYAs with cancer and the healthcare systems. This will be key to improving healthcare services, research, outcomes and policies for AYAs and to ultimately better cancer care for this patient group. To this aim, STRONG-AYA brings together an international multi-disciplinary consortium across seven European countries, led by the Netherlands Cancer Institute (NKI) and composed of academic research organisations (European Organisation for Research and Treatment of Cancer (EORTC), University of Southampton, University of Leeds, University of Manchester, Maastricht University, Netherlands Comprehensive Cancer Organisation (IKNL)), clinical partners (Italian National Tumour Institute, Léon Bérard Centre, Gustave Roussy Institute, Maria Sklodowska-Curie National Research Institute of Oncology, the Leeds Teaching Hospitals National Health Service Trust), stakeholder and patient organisations (Youth Cancer Europe, European Cancer Organisation) and a consulting company (FFUND). Building on previous initiatives, a STRONG-AYA data ecosystem will be set up for value-based care, research and policy for AYA with cancer by: 8 Ferrari A, Stark D, Peccatori FA et al. Adolescents and young adults (AYA) with cancer: a position paper from the AYA Working Group of the European Society for Medical Oncology (ESMO) and the European Society for Paediatric Oncology (SIOPE). ESMO Open 2021; 6: 100096. 9 Osborn M, Johnson R, Thompson K et al. Models of care for adolescent and young adult cancer programs. Pediatr Blood Cancer 2019; 66: e27991. 10 Fardell JE, Patterson P, Wakefield CE et al. A Narrative Review of Models of Care for Adolescents and Young Adults with Cancer: Barriers and Recommendations. J Adolesc Young Adult Oncol 2018; 7: 148-152. 11 Keegan TH, Lichtensztajn DY, Kato I et al. Unmet adolescent and young adult cancer survivors information and service needs: a population-based cancer registry study. J Cancer Surviv 2012; 6: 239-250. 12 Hayashi RJ. Adolescent and young adult cancer survivorship: The new frontier for investigation. Cancer 2019; 125: 1976-1978. 13 Saloustros E, Stark D, Michailidou K et al. Report on ESMO/SIOPE European Landscape project key results: Mapping the status and needs in AYA cancer care. Late-breaking and deferred publication abstracts public health 2017; 28, 5: V643. 14 Smith AW, Seibel NL, Lewis DR et al. Next steps for adolescent and young adult oncology workshop: An update on progress and recommendations for the future. Cancer 2016; 122: 988-999. STRONG-AYA – No. 101057482 – D1.10 1. Developing a Core Outcome Set (COS) specifically for AYAs with cancer, via a participative consensus process defining most important aspects for those directly affected by AYA cancer, including patients and healthcare professionals. 2. Implementing the COS across several national European healthcare systems. Data will be collected at local level and will then be included in a data integration platform. An overall ecosystem framework for data analytics and output will be created supporting federated analyses and the creation of reports across clinical and patient-reported data and making national repositories of (patient-reported) health data, available to individual patients, patient organisations, regulatory authorities, as well as the patients’ health care providers to inform clinical decision-making. The five resulting national ecosystems will be connected to each other into the pan-European ecosystem using a federated approach also utilizing the overall ecosystem framework. 3. Disseminating the COS to a wide range of local as well as pan-European stakeholders, in particular by developing analytical tools to process and present patient outcome data and establish feedback loops that inform patients and clinicians. Implementing these project objectives are five work packages within the STRONG-AYA project: • WP1: Development Core Outcome Set AYA with cancer and Data Collection (Lead: SOUTHAMPTON) • WP2: Governance, Data Security and Ethics (Lead: EORTC) • WP3: Infrastructure and Interoperability (Lead: UNIMAAS) • WP4: Operation of STRONG-AYA ecosystems, Stakeholder and Patient involvement, Dissemination, Exploitation, Communication (Lead: E.C.O.) • WP5: Scientific Coordination and Project Management (Lead: NKI) STRONG-AYA will enable AYA care and research to benefit from collection and pooling of patient-centered data and collaboration among all stakeholders: patients, healthcare professionals, scientists, and policymakers. More widely, the project will leverage the network of interested organisations and networks established under STRONG-AYA for long-term strengthened promotion of the necessary implementation of specialist AYA cancer services across Europe. This will ultimately bring novel insights into AYA cancer care, research and policy, contributing to the long-term improvement of outcomes for people with AYA cancer. 5 Study 2 initiation package The Netherlands Cancer Institute (NKI) is the Coordinator of STRONG AYA. As such it leads the STRONG AYA project and sets the precedent and scope of the next phase of the project, namely data collection of the COS. There have been delays in developing the COS in order to undertake the Delphi consensus process and to decide on the appropriate metrics. As such, at present time the NKI is the other centre to have secured ethics approval for the next phase of the project. There are several important contextual factors to consider at present regarding the ethics application for the STRONG AYA project. 1) Consent for the use of routinely collected data in research at the NKI, as a comprehensive cancer centre, is collected at patient registration, and thus no further patient consent is required to use data that is routinely collected in clinical practice and thus is available by data desk request from the electronic health record Protocol version 1.0 4 Stéphane Lejeune European Organisation for Research and Treatment of Cancer EORTC BE Maria Aguado European Organisation for Research and Treatment of Cancer EORTC BE Norbert Couespel European Cancer Organisation ECO BE Nora Lorenzo European Cancer Organisation ECO BE Miriam Romero European Cancer Organisation ECO BE Katalin Rizvine Lehoczky Fundatia Youth Cancer Europe YCE RO Urska Kosir Fundatia Youth Cancer Europe YCE RO Tessa van der Erve FFUND B.V. FFUND NL Marieke Dekker FFUND B.V. FFUND NL Protocol version 1.0 5 Summary Background STRONG-AYA is a new, interdisciplinary, multi-stakeholder European network to improve healthcare services, research and outcomes for Adolescents and Young Adults (AYA) with cancer, defined as individuals aged 15-39 years at cancer diagnosis. AYAs with cancer form a unique group; they face agespecific issues (e.g. infertility, unemployment, financial problems) and decreased quality of life due to cancer and its treatment. Unlike dedicated healthcare and trials for paediatric cancer patients, AYAspecific healthcare services are scarce and vary across Europe. AYAs who are at the core of society and economy need access to age-adjusted and high-quality healthcare. AYA-care and research will benefit from the collection, secure access, and integrative analysis of a large volume and highly inclusive pool of patient-centred data and collaboration among all stakeholders: patients, healthcare professionals, scientists, and policymakers. Within STRONG-AYA we will set up a value-based healthcare research ecosystem to develop data-driven, interactive policy and visualization tools that bring, in co-creation with all stakeholders including patients, novel insights into AYA healthcare. Objectives The overall project objectives include: (1) The development of an age-specific Core Outcome Set (COS) for AYAs with cancer (in process, approved by Southampton Ethics Committee/IRB 78653. Expected draft COS: December 2023); 2) The Implementation of the COS in 5 national healthcare systems (France, Italy, Netherlands, United Kingdom, Poland) and establishment of national infrastructures for the collection and management of outcome data; 3) The enactment of a pan-European STRONG-AYA ecosystem, including a privacy-preserving federated learning infrastructure; 4) The dissemination of the COS and its insights gleaned from the development of bespoke analytical tools to a wide range of local and pan-European stakeholders to use real world insight to develop data driven, value-based care and research across the continent. This IRB protocol concerns itself with objective 2 and is intended to operate as an umbrella or ‘master’ protocol for this objective at the pan-European level. Procedure and aims The primary aim of the STRONG-AYA consortium is to develop outcome prediction models (prevalence/incidence of, risk factors for and mechanisms of poor outcomes) for AYAs with cancer through the creation of national and pan-European federated learning infrastructure ecosystems. Once the draft COS has been finalised (December 2023), the COS will be implemented as a research instrument to gain real-world insight from AYA data (retrospective and prospective clinical and registry data, where relevant) and into clinical practice (prospective) by building a European healthcare research ecosystem for AYA with cancer. More specifically, we aim to develop outcome prediction models (prevalence/incidence of, risk factors for and mechanisms of poor outcomes) for AYA with cancer through the method of Federated Learning (FL). These models mean that analysis is based on data from patients aged 15-39 years at primary cancer diagnosis across multiple international centres, Protocol version 1.0 6 without any individual level patient data leaving the institution it originates from, therefore preserving patient data privacy. Conclusion We hypothesise that robust and generalisable FL can be developed across centres, and that this method will provide statistical models that explain the data, and demonstrate clinically useful risk factors for good and bad cancer outcomes. By linking multiple international centres, the FL models can be developed using the largest available cohort of AYA cancer patients to further develop research into AYA cancer and to better inform the care of this underserved cancer population. This has previously and recently been successful done for lung cancer patients (IRBd21-026_29-01-2021) and anal cancer patients (IRBd21-166_06-08-2021). Protocol version 1.0 7 1 BACKGROUND In any healthcare system it is essential that patients have access to high-quality care and to deliver tangible improvements in outcomes encompassing survival, health-related quality of life (HRQoL), the ability to attend school or work, get and raise children and actively participate in society [1]. This is particularly important for adolescents and young adults (AYA) with cancer, defined as 15 to 39 years at initial cancer diagnosis [2]. Their annual cancer incidence is 42.2/100.000, with 156.431 cases in Europe and 1.231.007 cases worldwide reported in 2018 (together 6.8% of all cancers) [3]. Advances in cancer treatment have led to increased survival rates and in AYA’s even over 80% will survive longterm (>5 years) [4], However, despite the relatively favourable cancer prognosis, AYA cancer patients are at risk of treatment related development of medical effects (e.g., cardiovascular disease or second malignancies), infertility or psychosocial effects (e.g., difficulty in romantic relationships, financial toxicity due to unemployment without a prior career job), and have an increased risk of late mortality [5, 6]. AYAs with cancer are distinct from the paediatric (<15 years) and the older adult (>40 years) cancer populations illustrated by the following findings [2, 7]: - Their unique spectrum of cancer types (epidemiology), with both paediatric-type and adulttype tumours [8]. The AYA group faces an overlap with paediatric tumours (brain tumours, sarcoma, leukaemia and lymphoma), but also with tumours common at older age (breast and increasingly colorectal cancer), and diagnoses which typically peak at AYA age (testicular cancer, thyroid cancer and melanoma). Hence, both paediatric oncologists’ input and adult oncologists’ competences are needed to deliver optimal care and treatment for AYAs. - Differences in tumour genomic, biology and clinical behaviour in AYA tumours compared to children and older adults [8, 9]. Age-specific molecular features are increasingly seen as therapeutically relevant. The biology of the host may also differ according to age, with distinct pharmacology and potential impact on therapy efficacy and toxicity profiles. Just translating the clinical management of children or older adults into the standards for the treatment of AYAs thus seems to be unjustified. - A lack of awareness that cancer may occur in this age group (among general population and healthcare professionals (HCPs)),with often results in diagnostic delays and/or difficult access to specialised care, potentially resulting in poor survival outcomes [10]; Diagnostic delay also has a negative impact on patients’ trust in the healthcare system and psychosocial outcomes such as anxiety. - A lack of AYA cancer patients’ participation in clinical protocols (reported rate of entering clinical trials ranged from 5% to 34% in published series), limiting the evidence base for treatments [11]; - Adolescence and young adulthood are complex phases of life due to the many physical, emotional, cognitive, and social transitions [12]. Important developmental tasks need to be achieved, such as forming one’s own identity and a healthy body image, establishing autonomy, responsibility and independence, finishing education and starting a career, starting a romantic relationship and having and raising young children [12]. A cancer diagnosis challenges AYAs’ abilities to achieve these developmental milestones [13]. The way in which AYA with cancer adjust to their cancer experience might have life-long implications for the quality of their survival [14]. Life-long consequences of treatment are often not part of the Protocol version 1.0 8 primary treatment discussions where the strong focus is on optimal survival outcomes. Examples of themes that AYA cancer patients would prefer to be discussed already very early after diagnosis are fertility, education and work, romantic relationships and sexuality, raising young children and financial consequences of disease and treatment. All topics that are not part of standard clinical consultations, due to lack of awareness, routine (as AYA cancer patients are rare), time constraints and lack of knowledge and supportive staff to discuss and act on these issues. - Historically, there was a lack of improvement in survival rates as compared to other age groups. For some tumour types, such as brain tumours and sarcomas, survival in AYA is still poorer than in children with the same disease [15] which is tumour biology, patient and treatment related. A MISSED CHANCE AND UNMET NEED: The unique characteristics require access to oncology services which provide expert cancer care and consider AYAs’ age-specific and complex psychosocial and physical needs regarding (1) physical changes, development of self-image, identity, relationships, sexuality and independence; (2) ageappropriate information and communication, shared decision-making, compliance and treatment adherence; (3) privacy and peer-support; (4) peculiar behaviours of this age and risk-taking (including alcohol/substance abuse). However, in many parts of the world, AYAs with cancer face inequities of care as they are poorly served by the traditional dichotomy of the integrated paediatric (“patient/family-centred”) care services versus dispersed (“disease-centred”) adult oncology services [11, 16, 17]. Up to half of AYA with cancer report unmet informational and service needs, impacting their direct (survival rates) and indirect (long term effects and mental health) recovery to participate in the society [18]. Cancer at AYA age is rare, although 4-6 times more frequent than paediatric cancer, but the rarity does not reflect the significant personal and societal costs of cancer in this population, as reflected in the potential years of life lost or saved; the decreased productivity and HRQoL due to the impact of the disease during formative years and long-term complications or disabilities [19]. The AYA Working Group (WG) of the European Society for Medical Oncology (ESMO) and the European Society for Paediatric Oncology (SIOP Europe) concluded in 2021 that finding rapid solutions to ‘speak the same language’ among healthcare professionals (HCPs) is essential to further improve health outcomes for AYAs [11]. The WG reported that standard clinical trial endpoints, such as five-year overall survival, progression-free survival, and cancer-specific survival, often do not address the specific needs of the AYA population. The WG found a widespread geographic variation, nationally and internationally, in AYA care programs with an unstructured, often merely philanthropic, funding [11]. When ESMO and SIOPE members were asked if their patients had access to specialized services for AYA with cancer, or if such services were in development, only 33% confirmed that they had, namely: 13% in Eastern and South-Eastern Europe, 45% in Western Europe and 60% in Northern Europe [20]. In addition, substantial inequalities in support by specialised HCPs, such as psychologists, social workers, physiotherapists, dieticians and AYA-dedicated nurses were found between AYA care programs [20]. The WG also reported an absence of outcome measures for monitoring and evaluating AYA cancer care programs and control [11]. In 2016, the NCI updated the AYA cancer progress review group report and examined scientific gaps and opportunities for future AYA oncology [22]. It was concluded that Protocol version 1.0 9 one of the most important contributions to AYA research would be to pool data (e.g. patient-reported outcomes, clinical and treatment data) across institutions and countries and create large cohorts for researchers to address the burden of cancer in AYA [22]. STRONG-AYA seeks to take up this call from the ESMO-SIOPE WG and NCI to establish a core outcome set (COS), and to use real-world data, pooled in a federated learning infrastructure, to comprehensively assess patients’ age-specific needs, screen for physical and psychosocial problems and provide multidisciplinary, holistic, age-specific hospital and community support. By evaluating AYA cancer patients’ healthcare experiences and outcomes we believe their care and outcomes can be improved and unjustified variations in quality of care reduced. We believe that this can be done by maximizing the potential of multi stakeholders’ data. Although an ever increasing amount of data is available, the collection, access, processing, and use of these data are still very fragmented within and especially across national health systems. There is a lack of data standardization, data interoperability and (prospective) collection of outcomes of relevance for AYAs with cancer. The development and implementation of a COS, a consensus-based agreed minimum set of outcomes that should be measured and reported, with patient-centred outcomes of value for AYAs with cancer, represents an opportunity to enable data-driven healthcare innovation and serve as a basis to address clinically relevant questions for this vulnerable patient group. The creation of STRONG-AYA as a new dedicated, interdisciplinary, multi-stakeholder European network, consisting of AYAs with cancer, HCPs working in this field, researchers and policy-makers, builds on previous initiatives, such as the European Network for Cancer Research in Children and Adolescents program (ENCCA), a specific European Network for Teenagers and Young Adults with Cancer (ENTYAC; EU FP7 2011-14). STRONG-AYA: We have united a network of professionals (HCPs and scientists) and patients, some of which are already collaborating within ENTYAC and the ESMO/SIOPE AYA WG, who collectively expressed their wish to join forces to work on the specific challenges of AYA with cancer. The time is right to make a significant investment to sustainably align research and healthcare to inform individual decision-making and healthcare policy. By creating five national ecosystems and an overall European AYA healthcare research ecosystem, concentrating on the dynamic generation and use of outcome data by all important actors within healthcare and research, we will work towards the most effective, affordable and sustainable value-based care for AYA with cancer to maximize their health outcomes. Within STRONG-AYA we will make use of federated learning to implement the COS and create the national and pan-European ecosystem. Conventional data analysis requires sharing and centralization of data. But, combining data originating from multiple sources is difficult because of ethical, administrative, legal, and political barriers associated with data sharing [23]. In order to avoid these issues, we will use a hybrid model of centralised and federated analysis or learning techniques. Centralised approaches will mainly be applied in the local ecosystems, while federated approaches are specifically relevant for learning between ecosystems at a pan-European and the national level. Federated analysis/learning is an Artificial Intelligence technique – i.e. machine learning – that reformulates conventional data analysis algorithms so that data centralization becomes unnecessary and consequently data transfer and associated agreements are not needed [24]. Federated analysis/learning is defined as analysing or learning from data without data leaving the source: algorithms iteratively analyse separate data sources (sites) and only aggregated statistics are Protocol version 1.0 10 produced as outputs with the outside world [24]. In other words: research questions and answers are shared between the databases instead of the data. Federated analysis/learning is a sustainable approach for AYA data as it offers a privacy-preserving solution to combine dispersed data to yield orders of magnitude more data than traditional approaches [24]. The federated analysis/learning methodology requires and forced the development of data with semantic interoperability: FAIR data [25]. An advantage of federated analysis/learning is that it makes implementation of models in daily clinical practice possible (e.g. clinical decision support systems for diagnostic decision-making), thereby facilitating a rapid learning healthcare practice [26]. Protocol version 1.0 11 2 STUDY OBJECTIVES The primary aim of the STRONG-AYA consortium is to develop outcome prediction models (prevalence/incidence of, risk factors for and mechanisms of poor outcomes) for AYAs with cancer through federated learning (FL). These models will inform further AYA cancer research and establish best practice in care. The FL method will describe and model the relationships between the key elements of data from patients aged 15-39 years at primary cancer diagnosis across multiple international centres under their local, valid ethical approval. The FL method enables the research team to achieve this without any individual level patient data leaving the institution it originates from, therefore preserving patient data privacy. The scope of this protocol is, jointly, the collection of data determined by the COS development and the building and implementation of the STRONG AYA FL infrastructure at the NKI. At ime of IRB submission (July 2023) we currently intend to apply to only collect data as confined by the TADP. If or when data beyond the TADP is desired for STRONG AYA, a new protocol or amendment (in accordance to IRB guidelines) will be developed. The following is required to reach the aforementioned objectives: 1. Establish a COS of outcomes and variables for data collection and measurement o This is in progress and the draft COS is expected to be completed by the end of 2023. The COS is being developed via a systemic literature review, qualitative interviews with patients, HCPs, and caregivers, and a consensus-building Delphi process. This process is defined by the protocol paper and ethics approval (78653) of the part of the STRONG-AYA study defining the COS based primarily at the University of Southampton. This protocol outlined the scope and need for a COS; assembled a working group; developed a study protocol encompassing a systemic literature review, qualitative interviews and a Delphi study in alignment with the EU CAYAS NET study (https://ec.europa.eu/info/fundingtenders/opportunities/portal/screen/how-to-participate/orgdetails/997929890/project/101056918/program/43332642/details) to build multistakeholder consensus; as well as metrics and case-mix variables. Refinement of the draft COS will take place after 2023. 2. Establish national ecosystems in each of the five participating countries (Netherlands, United Kingdom, France, Italy, and Poland), consisting of a) An interdisciplinary, multi-stakeholder AYA cancer network of experts to facilitate collaboration, dissemination and communication, as well as the day-to-day collection of AYA patient data via routine clinical care in electronic health records (EHRs), validated patient-reported outcome (PRO) questionnaires, etc. b) A technical infrastructure and tools for data management that use federated learning in line with FAIR (Findable, Accessible, Interoperable, Reusable) data principles (In progress, currently defined by the Data Management Plan, technical blueprint, and developing operational plans for the various ecosystems). It is envisioned that this technical infrastructure will include integrated web-portals with various and appropriate levels of access and permissions for use by various stakeholders including HCPs, patients, and policymakers Protocol version 1.0 12 c) A governance model and legal and framework to ensure compliance with European and each country’s legal and policy stipulations regarding the collection, use and sharing of health outcomes data (e.g. robust data protection and General Data Protection Regulation (GDPR) compliance d) Secure and locally controlled data warehouses of local data resources that individual partners are able to access solely by themselves as independent institutions, such as:  research databases,  clinical trials case reports,  cancer registries,  hospital-based electronic health records,  repositories of patient (or self) reported outcomes, and  other such databases that the Partner deems relevant for the STRONG-AYA e) Sustainability model plan to ensure long-term sustainability of the ecosystems to support European/national/regional/local cancer policy organisations to build appropriate AYA cancer services 3. In parallel, to establish a pan-European umbrella ecosystem to manage consistency and interoperability across national ecosystems, to serve as a European gateway, and to support the creation of ecosystems in other European countries. 4. To conduct the following activities when the national ecosystems become operational: a) Retrospective data (mainly clinical) will be collected from national and regional registries or previously conducted ethically approved population-based studies, this means data have to be standardized and mapped on a common data model to integrate them in the infrastructure to be used for analysis and outcome reports. b) Prospective COS data (clinical and patient-reported) will be newly collected in participating clinical centres among newly diagnosed AYA with cancer; c) Retrospective COS data (clinical and patient-reported) will be collected in participating clinical centres (survivors); We hypothesise that robust and generalisable federated models can be developed across countries, and that these models will demonstrate clinically useful prevalence/incidence rates, risk factors and mechanisms of poor outcomes as defined in the COS. By linking multiple international centres, the federated models can be developed using the largest available cohort of AYA cancer patients. Protocol version 1.0 13 Project timelines: Task Q4 '22 Q1 '23 Q2 '23 Q3 '23 Q4 '23 Q1 '24 Q2 '24 Q3 '24 Q4 '24 Q1 '25 Q2 '25 Q3 '25 Q4 '25 Q1 '26 Q2 '26 Q3 '26 Q4 '26 Q1 '27 Q2 '27 Q3 '27 Q4 '27 WP1: Development COS and data collection COS development: Convene stakeholders, leverage literature and build consensus via the Delphi panel Digital technology requirements and design of reports (qualitative research informing technical functionality of STRONG AYA infrastructure) Implementation of COS and data collection at participating centres COS revision and refinement Stratification and outcome prediction WP2: Governance, data security and ethics Ecosystems governance model and business architecture Patient - centred and patient - informed ethical guidance (formerly Stakeholder value) Governance, data protection and ethics WP3: Infrastruct ure and Architecture blueprint development Patient tool development Protocol version 1.0 20 Protocol version 1.0 21 5 Data flows and federated learning infrastructure Following a similar rationale to the atomCAT2 study, sharing data insight and cooperation in multicentre studies is invaluable for the development and validation of prognostic models in rare cancers, which by definition encompass all AYA cancers. Federated learning infrastructures and the data flow principles behind it ensure data insights can be shared whilst preserving patient privacy and local autonomy over data. Furthermore, the agile nature of federated learning allow insights to be drawn whilst working with, not against, the diverse local contexts and situations around data collection at each participating centre. Data flows: Data flows within the STRONG-AYA consortium, and at the NKI, will follow the following principles: Each Partner controls and operates its own national or local ecosystem. This is expected to consist of, but is not exclusively limited to, local data resources that the Partner is able to access solely by themselves as independent institutions, such as: • research databases, • clinical trials case reports, • cancer registries, • hospital-based electronic health records, • repositories of patient (or self) reported outcomes, and • other such databases that the Partner deems relevant for the STRONG-AYA as per the COS These “grassroots” data sources are allowed to be either retrospective, or prospective, or a mixture of both. Since each Partner owns, controls and operates in their own space, they will autonomously decide when and which Data to make accessible for Federated Learning through the STRONG-AYA consortium. There is no intellectual, technical or consortium-derived mandatory requirement on every Partner to make all Data completely accessible at exactly the same time; noting, as mentioned above, that the data collection paradigm must allow for dynamism, adaptability and step-by-step accumulation (and maturation) of the Data over time. Each Partner will be responsible for requesting individual-level subject data from primary data sources within their own area of control (as above, the electronic health records, cancer registries, etc. etc.) using local governance mechanisms and technical instruments that are feasible for the Partner. These mechanisms and instruments may, for illustration purposes only, include Data Transfer Agreements between themselves and national cancer registries, and customized data extraction tools from electronic health records hosted in their local hospital (see, for a purely illustrative example, Figure 1 below). Existing governance and instruments should be re-used wherever possible, with a view to grow and sustainably reach a better quality of data collection over time. Protocol version 1.0 22 Figure 1: data flows for STRONG AYA Each Partner stores pseudonymized data they have extracted from their local sources into a secured computation device which is within their institutional data security firewall. This device resides on a sub-network that can be insulated from other mission-critical and operational systems used by the institution. The Partner needs to ensure sufficient security for the private data in their own collection, using the advice of their local data protection officers and information security teams. If a Partner uses pseudonym keys to link information of the same human subject from multiple data sources, such key files must be stored on a separate device from the Data itself. Traditionally, machine learning models are trained on data that are collected centrally from multiple sources. However, the ethical, legal and societal implications regarding sharing of data outside the source organization has led to a paradigm shift in how machine learning models are trained. Instead of sharing data, algorithms are sent to each of the data sources, where they are trained locally. The locally trained algorithms are aggregated to develop a global model in a manner as if the algorithm is trained by traditional approaches. The privacy and confidentiality of data is protected at the source and only necessary analysis is shared. Protocol version 1.0 23 Federated learning Figure 2: Principle parts of federated learning STRONG-AYA will use the Personal Health Train (PHT) paradigm to create its federated learning infrastructure. The Personal Health Train (PHT) is a privacy-by-design infrastructure for performing federated/distributed machine learning. The data providers (hospitals) can participate in multicentre data analysis without exposing sensitive data outside the organization. The principle of PHT can coexist with other privacy enhancing measures such as encrypted and perturbed data, but the crucial point here is that the PHT paradigm never relies solely on the unbreakability of encryption nor the irreversibility of perturbation to safeguard patient privacy. PHT ensures that the machine learning process is completed in a data agnostic manner. The data station provides an execution platform for the algorithm and provides secure access to the data repository. In the PHT infrastructure, the metaphor ‘train’ refers to the Docker containers containing the data query and the algorithm. These containers provide an isolated and secure environment for the query and algorithm. ‘Tracks’ are the secured communication channels connecting the central message broker, the researcher and the data stations. Trains are sent to the data station through the tracks and only authenticated users are allowed to trigger a federated learning. The open source implementation of PHT, Vantage (https://vantage6.ai/) will be used as the software solution for performing privacy preserving federated machine learning on the datasets. Protocol version 1.0 24 Figure 3: PHT query journey The PHT was developed by experts at the IKNL and the University of Maastricht and has been applied in numerous oncological use-cases in the Netherlands and internationally. Selected projects include PROSPECT, a prostate cancer study, of which NKI-AvL is a collaborator; rare cancer registry developments such as RARECANnet Asia and BLUEBERRY (IKNL), the atomCAT anal cancer study (AvLNKI). The specific computing resources required for STRONG-AYA are outlined in the technical blueprint attached which is the evolving standard operating procedure defining the integrity and safety of the system alongside the Data Management Plan. In the proposed federated structure, the exchange of statistical summaries and model coefficients (e.g., odds ratio) are as close as possible to anonymization without becoming unfit for the purpose of actionable insights and testable hypotheses to improve the care of AYAs with cancer. In so far as the same such statistics and results are printed in public report and articles, then the information exchanged in federated learning is NOT any more identifiable than articles and reports. Safety and integrity of the local data spaces is the responsibility of the local PI and his/her IT team. Safety and integrity of the federation cross-institutional communications networks will be the responsibility of Medical Data Works, who have been subcontracted to host the STRONG-AYA central server. The design of the software safeguards and the algorithmic integrity is a joint undertaking of UNIMAAS and IKNL. Protocol version 1.0 25 6 Data analysis Sample size: As previously mentioned, since the main aim of this study is to implement the COS, no formal sample size calculation will be done and will be dependent on the specific sub-question on analysis undertaken by researchers using the STRONG AYA ecosystem From all AYA with cancer diagnosed in the STRONG-AYA centres, we expect that the prospective part of STRONG-AYA will be available to around 4000 patients each year (please see the Table below) that will be followed longitudinally over time (each year). This number will only grow when STRONG-AYA will open in other countries. When patient inclusion for the prospective part of the data collection is not possible directly after diagnosis, it is also possible to include patients or survivors later in their patient journey (retrospective clinical practice). We will aim for a response rate of 25%. AYA Cancer patients per institution based on historical data Short Name Historical numbers (retrospective) New cases expected per year (prospective) IRCCS 2000 400 (primary focus on sarcomas; breast, testicular and melanoma) UL 6000 600 (all tumour types) MU 2000 355 (primary focus on Breast, Gynae cology , Sarcoma, Germ cell, CNS) MSCN RIO 600 150 (primary focus testicular cancers, sarcomas) I GR 200 0 800 (all tumour types) CLB 2000 150 (all tumour types) NKI 4000 500 (all tumour types) YCE 12775 >1000 (all tumour types) With regard to retrospective registries/population-based study data: As an important step towards the development of future personalised prediction models, STRONG-AYA will also utilise data from the existing databases available within its consortium (e.g. in The Netherlands: clinical data from the Netherlands Cancer Registry and patient-reported outcomes via the PROFILES registry of over 4000 AYA who were diagnosed with cancer 5-20 years ago, as well as the SURVAYA dataset (IRBd18-122); in UK: clinical data from the National Cancer Registry). Statistical analysis: A full data analysis plan will be developed prior to data analysis initiation and will be pre-registered in a relevant public repository (e.g. Open Science Foundation, https://osf.io). As the research questions applied to STRONG AYA will be highly variable, this document will be dynamic and ever-evolving. Protocol version 1.0 26 Descriptive data analysis: prevalence/incidence poor outcomes Summary statistics will be exchanged between centres in order to calculate prevalence/incidence rates of poor outcomes and explore cohort differences prior to modelling. Categorical variables will be compared using chi-square test, and numerical variables will be compared using a one-way ANOVA test. All tests will be carried out using summary statistics (number of patients, mean and standard deviation values) rather than individual patient data. Estimated survival / recurrence rates and potential follow-up times will be calculated by each centre individually, using the Kaplan-Meier estimator. The median follow-up time will be calculated based on the inverse Kaplan-Meier estimator. A detailed approach to handling missing values, on a withinand between-centre basis, will be specified in the data analysis plan. Risk factors and mechanisms Already-established predictive and prognostic factors for the outcomes in question will be identified through a systematic review of the literature. This approach identified the initial list of relevant data to be collected; this was subsequently prioritised in a Delphi study, and additional factors were added. A final plan for factor selection and model refinement will be available in the data analysis plan. (multivariate) Linear and logistic regression analyses for continuous and dichotomous outcomes respectively, and Cox regression for time-dependent outcomes will be used. Moderation and mediation effects will be explored, depending on research question. Multivariate analyses will be adjusted for identified case-mix factors. Protocol version 1.0 27 7 ETHICAL CONSIDERATIONS This study protocol assumes standard of care is provided to AYA cancer patients, there is no clinical intervention performed by or within this protocol. Therefore, no informed patient consent is needed to collect the data described in this protocol. Each institution will acquire separate local approvals for accessing and collecting patient data for research; the local coordinating investigator will be responsible for providing a copy of the letter confirming that use of data for research is approved (e.g. from Institution Review Board, IRB), including approval reference number. As no individual patient data will be exchanged between institutions, no data transfer agreements or additional patient consent will be needed. However, in caution to mitigate privacy risks, a Joint controllership agreement will be drafted between all partners of the STRONG AYA consortium prior to data collection. Local information governance (IG) and data protection review of the distributed learning infrastructure may be needed, and should be obtained wherever appropriate. The study coordinators may be able to assist with supporting material. A pan-European ROPA and DPIA has been conducted and circulated to all STRONG AYA consortium members to review and sign. It is expected to be a dynamic document that evolves with the project over time to ensure best practice regarding data security. Protocol version 1.0 28 8 ORGANISATION AND POLICIES Study oversight and management Details of the consortium engagement and project management are described in detail in a collaborative research agreement and the consortium agreement. In brief, the consortium consists of the senior investigators, co-investigators, and local institutional participants. Consortium membership will be inclusive, with all individuals contributing (e.g. to local institutional work) eligible, but each centre will be asked to name a single centre lead who will take final responsibility for centre contribution. Day-to-day management will be handled by the study coordinator, supported by the consortium leadership team (senior investigators and co-investigators). This group will meet regularly to ensure smooth study conduct and communication. The study coordinator meets with the involved parties of each work package monthly to stay on top of activities and concerns and reports weekly to the lead PIs. A detailed reference regarding the project’s decision making structures, communications guidelines, quality assurance for deliverables, conflict resolution and risk management plans, as well as other policies and procedures, have been incorporated into the Project Handbook. Additional online meetings for the full consortium will provide study oversight. As patient-centred research is a tenant of the project’s objectives and ethos, a Patient Advisory Board is currently being recruited to provide patient advice on STRONG AYA’s activities. This is further complimented by an Ethics and Regulatory Advisory Board and a Scientific Advisory Board to ensure that STRONG AYA does not exist in an intellectual silo and is accountable to experts in the relevant areas. Publication policy STRONG AYA’s authorship policy follows the accepted principles for establishing authorship according to the International Committee of Medical Journal Editors which defines the four following criteria for claiming authorship:  Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work;  Drafting the work or revising it critically for important intellectual content;  Final approval of the version to be published;  Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The contributions of authors should be identifiable, and authors should have confidence in the contribution of co-authors. Authorship positions and the corresponding author should be decided before the work is completed and with consensus among the parties. If conflict arises, the matter will follow the internal conflict resolution pathway. All parties listed as authors should meet all four of the criteria outlined in the ICMJE guidelines. The corresponding author should make sure that they are available throughout the submissions process to respond to editorial queries and reviewer’s comments in a timely manner. The authorship criteria is not intended for use to disqualify STRONGAYA colleagues from authorship who otherwise meet authorship criteria by denying them the opportunity to meet the second and third criteria. In addition to listing authors, all scientific publications stemming from STRONG AYA will acknowledge the consortium via the use of an Protocol version 1.0 29 ‘acronym’ or statement following the authorship list “...on behalf of the STRONG-AYA consortium”. A full list of STRONG-AYA contributors, by institution, will be listed in the acknowledgements of publications. This list will be reviewed before publication submission to ensure it is up to date. Authors are expected to acknowledge non-academic support as well where possible, including but not limited to those who have provided materials or methods, organizational support, technical support, clinical cases, patients and their relatives, funding bodies, etc. All successful publications should be reported to the Project Coordinator for inclusion in the dissemination tracker. For the primary study publications, we plan to name the senior investigators and co-investigators, and one local lead per institution as co-authors. We will apply for a consortium “group” authorship, and within this group authorship, we will add the names of each additional person that has contributed in a meaningful way to this project, including all relevant consortium members. Infrastructure user agreement Medical Data Work BV (MDW, https://medicaldataworks.nl/) implements a privacy preserving distributed infrastructure that investigators in STRONG-AYA will use. Therefore, an Infrastructure User Agreement (soon to follow) is required as a contractual agreement between each institution and MDW, and the same agreement is required between the principal investigators and MDW. MDW will not be considered as a “processor” of clinical data according to the definition in the EU General Data Protection Regulation, but is solely the provider of the infrastructure. As the infrastructure provider, MDW will enforce the legal use of algorithms and data stations, and this agreement shall define the terms and conditions for the use of the infrastructure. A template Infrastructure User Agreement (from MAASTRO) will be provided to all partners in the project. Protocol version 1.0 36 Definitions STRONG AYA consortium members are referred to as following within this text: 1. NKI-AVL – Stichting het Nederlands Kanker Instituut – Antoni van Leeuwenhoek Ziekenhuis (NL) 2. YCE – Youth Cancer Europe (RO) 3. INT – Fondazione IRCCS Instituto Nazionale dei Tumori (IT) 4. FFUND – FFUND BV (NL) 5. CLB – Centre de Lutte Contre le Cancer Leon Berard (FR) 6. ECO – European Cancer Organisation (BE) 7. UNIMAAS – Universiteit Maastricht (NL) 8. IKNL – Stichting Integraal Kankercentrum Nederland (NL) 9. EORTC – European Organisation for Research and Treatment of Cancer AISBL (BE) 10. IGR – Institut Gustave Roussy (FR) 11. MSCNRIO – Narodowy Instytut Onkologii im. Marii Sklodowskiej-Curie – Panstwowy Instytut Badawczy (Marie Sklodowska-Curie National Research Institute of Oncology) (PL) 12. UOM – University of Manchester (UK) 13. UOL – University of Leeds (UK) 14. LTHT – Leeds Teaching Hospitals National Health Service Trust (UL) 15. SOUTHAMPTON – University of Southampton (UK)  Grant Agreement (including its annexes and amendments): the agreement signed between the beneficiaries of the HORIZON Research and Innovations Actions (hereafter referred to as Horizon) and the European Health and Digital Executive Agency (hereafter referred to as HADEA) for the undertaking of the STRONG AYA project (Grant Agreement no. 101057482).  Beneficiary: Signatories of the Grant Agreement  Associated Partner: Entities which participate in the action but without the right to charge costs or claim contributions.  Project: the sum of all activities carried out in the framework of the Grant Agreement.  Consortium: the STRONG AYA consortium, including all the aforementioned partners.  Consortium Agreement: The agreement made between STRONG AYA members for the implementation and execution of the action outlined in the Grant Agreement. The agreement shall not affect the parties’ obligations to HADEA on behalf of the European Union, and/or to one another arising from the Grant Agreement.  Pseudonymisation: the processing of personal data in such a manner that the personal data can no longer be attributed to a specific person, including patients, without the use of additional information, provided that such additional information is kept separately and is subject to technical and organisational measures to ensure that the personal data are not attributed to an identified or identifiable natural person in the context of the STRONG AYA project. Protocol version 1.0 37 Abbreviations Acronym/Abbreviation Meaning DMP Data Management Plan FAIR Data principles of Findability, Accessibility, Interoperability, and Reusability HCP Health Care Provider PRO Patient Reported Outcome COS Core Outcome Set PROM Patient Reported Outcome Measure ROPA Records of Processing Activities DPIA Data Protection Impact Assessment GDPR General Data Protection Regulation WP1 Work Package 1 ( Development Core Outcome Set AYA with cancer & data collection) WP2 Work Package 2 ( Governance, Data Security and Ethics) WP3 Work Package 3 ( Infrastructure and Interoperability) WP4 Work Package 4 ( Operation of STRONG AYA ecosystems, stakeholder and patient involvement, dissemination, exploitation, communication) WP5 Work Package 5 ( Scientific coordination and project management) Protocol version 1.0 38 1. Introduction 1.1. Background: adolescents and young adults with cancer STRONG-AYA is a new, interdisciplinary, multi-stakeholder European network to improve healthcare services, research and outcomes for adolescents and young Adults (AYA) with cancer, defined as individuals aged 15-39 years at cancer diagnosis. AYAs with cancer form a unique group; they face age-specific issues (e.g. infertility, unemployment, financial problems) alongside decreased quality of life due to cancer and its treatment. Unlike dedicated healthcare and trials for pediatric cancer patients, AYA-specific healthcare services are scarce and vary across Europe. AYAs, who are a very important social and economic demographic group, , need access to ageadjusted and high-quality healthcare. AYA care and research will benefit from collection and pooling of patient-centered data and collaboration among all stakeholders. Cancer at adolescent and young adult (AYA) age is rare, although 4-6 times more frequent than paediatric cancer (i.e. prepubescent period). However, this rarity does not reflect the significant personal and societal costs of cancer in this population, as reflected in the potential years of life lost or saved, the decreased productivity and quality-of-life due to the impact of the disease during formative years, and the long-term complications or disabilities1. AYAs with cancer form a unique group; they face age-specific issues (e.g. infertility, unemployment, financial problems) and decreased quality of life due to cancer and its treatment. Unlike dedicated healthcare and trials for paediatric cancer patients, AYA-specific healthcare services are scarce and vary across Europe. AYAs who are at the core of society and the economy need access to age-appropriate and high-quality healthcare. Defining AYAs with cancer as 15 to 39 years at initial cancer diagnosis2, their annual cancer incidence is 42.2/100.000, with 156.431 cases in Europe and 1.231.007 cases worldwide reported in 2018 (together 6.8% of all cancers)3. Population-based data from 27 European countries supports that AYAs have lower survival than children but higher than adults affected by cancer. Advances in cancer treatment have led to increased survival rates for AYAs with cancer, improving by 82% for all cancers between 1990 and 20074. However, survival improvement in AYA is more challenging than for children and older cancer survivors, perhaps because AYA have the highest absolute excess risk of second primary malignant neoplasms5. AYA face some distinct challenges given that they belong to neither paediatric nor adult oncology groups. Characteristic features of this population group include unique spectrum of cancer types, different tumour biology, unique complex psychological needs, distinct late sequelae, including impaired fertility, and palliative care. These traits imply that clinical management, treatment, diagnosis, psychological support will need to be designed and developed for AYA’s specific needs. For example, AYAs diagnosed with breast and prostate carcinomas have worse survival than older patients because of the biological differences between them, highlighting 1 Stoneham SJ. AYA survivorship: The next challenge. Cancer 2020; 126: 2116-2119. 2 Adolescent and Young Adult Oncology Review Group. Closing the gap: Research and Care Imperatives for Adolescents and Young Adults with Cancer. National Institute of Health, National Cancer Institute, and Livestrong Young Ault Alliance: Bethesda, MD, USA, 2006. 3 Trama A, Botta L, Steliarova-Foucher E. Cancer Burden in Adolescents and Young Adults: A Review of Epidemiological Evidence. Cancer J 2018; 24: 256-266 4 Trama A, Botta L, Foschi R et al. Survival of European adolescents and young adults diagnosed with cancer in 2000-07: population-based data from EUROCARE-5. Lancet Oncol 2016; 17: 896-906. 5 Keegan THM, Bleyer A, Rosenberg AS et al. Second Primary Malignant Neoplasms and Survival in Adolescent and Young Adult Cancer Survivors. JAMA Oncol 2017; 3: 1554-1557. Protocol version 1.0 39 the need to target screening methodologies, treatment and policies to their needs6. AYAs with cancer also face significant psychological challenges, including substance abuse, mental health issues, suicidal ideations and increased emotional burden from cancer and cancer-related morbidity. Finally, tailoring cancer care to AYA’s needs is difficult and due to many different complex factors including the low rate of participation by AYAs in clinical trials and cancer research7. Despite the increasing awareness and a growing body of scientific literature, these unique issues are not yet fully recognised and addressed by the European health systems and AYAs with cancer are frequently underserved. In part, this may have resulted from the traditional dichotomy between the integrated paediatric (“patient/family-centred”) care services versus dispersed (“diseasecentered”) adult oncology services8,9,10. Up to half of AYAs with cancer report unmet informational and service needs, impacting their direct (survival rates) and indirect (long term effects and mental health) recovery to participate in society11. Furthermore, aligned with this barrier is the low rate of health care utilisation by AYAs, especially primary care, given their challenges to sustain health insurance coverage12. According to a survey conducted through the networks of the AYA Working Group of the European Society for Medical Oncology (ESMO) and the European Society for Paediatric Oncology (SIOP Europe), 67% of practitioners do not have access to specialised centres for AYA with cancer, 67% had no access to a specialist cancer service for late effects management and 38% had no access to fertility specialists. Under-provision and inequality of AYA cancer care is common across Europe and especially in the Eastern and Southern-East. Furthermore, the Working Group also reported an absence of outcome measures for monitoring and evaluating AYA cancer care programs and control13. Among the recommended future steps, it has been identified that one of the most important contributions to AYA research would be to pool data (e.g. patient-reported outcomes, clinical and treatment data) across institutions and countries and create large cohorts for researchers to address the burden of cancer in AYA14. There is a lack of data standardization, data interoperability and (prospective) collection of outcomes of relevance for AYAs with cancer. 1.2. Project aims The STRONG-AYA project aims to tackle the underrepresentation of AYA’s experiences and outcomes when navigating the healthcare system and in clinical care by developing national infrastructures for outcome data management and clinical decision-making within a pan-European ecosystem and establishing communication feedback for AYAs with cancer and the healthcare systems. This will be 6 Stark D, Bielack S, Brugieres L et al. Teenagers and young adults with cancer in Europe: from national programmes to a European integrated coordinated project. European Journal of Cancer Care, 25(3), 419–427. 7 Hayashi RJ. Adolescent and young adult cancer survivorship: The new frontier for investigation. Cancer 2019; 125: 1976-1978. 8 Ferrari A, Stark D, Peccatori FA et al. Adolescents and young adults (AYA) with cancer: a position paper from the AYA Working Group of the European Society for Medical Oncology (ESMO) and the European Society for Paediatric Oncology (SIOPE). ESMO Open 2021; 6: 100096. 9 Osborn M, Johnson R, Thompson K et al. Models of care for adolescent and young adult cancer programs. Pediatr Blood Cancer 2019; 66: e27991. 10 Fardell JE, Patterson P, Wakefield CE et al. A Narrative Review of Models of Care for Adolescents and Young Adults with Cancer: Barriers and Recommendations. J Adolesc Young Adult Oncol 2018; 7: 148-152. 11 Keegan TH, Lichtensztajn DY, Kato I et al. Unmet adolescent and young adult cancer survivors information and service needs: a population-based cancer registry study. J Cancer Surviv 2012; 6: 239-250. 12 Hayashi RJ. Adolescent and young adult cancer survivorship: The new frontier for investigation. Cancer 2019; 125: 1976-1978. 13 Saloustros E, Stark D, Michailidou K et al. Report on ESMO/SIOPE European Landscape project key results: Mapping the status and needs in AYA cancer care. Late-breaking and deferred publication abstracts public health 2017; 28, 5: V643. 14 Smith AW, Seibel NL, Lewis DR et al. Next steps for adolescent and young adult oncology workshop: An update on progress and recommendations for the future. Cancer 2016; 122: 988-999. Protocol version 1.0 40 key to improving healthcare services, research, outcomes and policies for AYAs and to ultimately better cancer care for this patient group. AYAs, as a unique socio-economic group, need access to age-adjusted and high-quality healthcare. AYA care and research will benefit from collection and pooling of patient-centered data and collaboration among all stakeholders: patients, healthcare professionals, scientists, and policymakers. Our consortium includes clinical and scientific leaders in AYA-care, data science and registries, The European Cancer Organisation (ECO), Youth Cancer Europe (YCE) and the European Organisation for Research and Treatment of Cancer (EORTC), building on previous initiatives and EU grants, and merging expertise with innovation. Within STRONG-AYA, we will set up a value-based healthcare research ecosystem to develop data-driven, interactive policy and visualization tools that bring, in co-creation with all stakeholders including patients, novel insights into AYA healthcare. This will require the establishment of symbiotic, independent, not-for-profit systems of working based at the local level across the five health services currently participating in STRONG AYA, as well as a panEuropean ecosystem to manage the connections between them. The ecosystem business architecture deliverable will cover the following aspects of the organisational and design aspects of the STRONG AYA ecosystems:  The STRONG AYA vision  Governance key principles that guide the establishment and management of the STRONG AYA ecosystems, including present and future participating ecosystems  The legal structure underpinning the formation of the STRONG AYA network at both national and pan-European levels  A synopsis of the data access and flows in the network  The organisational aspects and responsibilities of the ecosystems  A cursory sketch of how STRONG AYA ecosystems may be sustained beyond the funding period Given the interconnected nature of the STRONG AYA’s work packages, this deliverable pulls on work undertaken across several of its workflows: WP2, WP3, and WP4. It is the encapsulation of the work undertaken thus far and therefore should be viewed as a living document that will evolve over time. 2. Methods and materials The WP2 leads, the EORTC, along with input from colleagues at the Brightlands Institute for Smart Society at Maastricht University (BISS) and the University of Leeds (UoL) designed a questionnaire to assess the local legal processes and governance contexts within each partner institution to establish an initial comprehensive understanding of what the STRONG AYA governance and legal structures should entail. This is necessary to meet the objectives of the project in terms of data delivery, technology, and impact whilst maintaining compliance. Protocol version 1.0 41 The work package collaboratively developed questionnaires to gather information on the local institutional and national regulations, procedures and processes around data security and flows. This was then expanded upon using in depth detailed on-one-one meetings between WPLs and each individual data-contributing partner :  The Netherlands Cancer Institute (NKI) based at the Antoni van Leeuwenhoek Hospital in Amsterdam  The Marie-Sklodowska-Curie National Institute of Oncology (MSCNRIO) in Warsaw  The Instituto Nazionale dei Tumori (INT) in Milan  Institut Gustave Roussy in Paris  Centre de Lutte Contre le Cancer Leon Berard in Lyon  The Christie NHS Foundation Trust (a hospital trust affiliated with the University of Manchester) in Manchester  The Leeds Teaching Hospital NHS Trust (a hospital trust affiliated with the University of Leeds) in Leeds This establishes:  What are the common elements of AYA healthcare data collected and feasibly collected by project partners (WP1)  Consensus and preliminary Tier 1 list of minimum COS, to lay the foundation for future Delphi-style consensus on upgraded extended COS (WP1)  Existing legal, governance and data management procedures that are already in place at partner institutions (WP2, WP3)  the degree of understanding of federated research (data accessing) ecosystems, and how these can fit within the regulatory interpretation of the participating partners (WP2, WP3)  the extent to which the existing research and operational infrastructures can be integrated with the STRONG AYA vision (WP3)  level or degree of data preparedness (and hence data preparation needed) in order to establish the healthcare of AYA persons needed for this project (WP3) In addition to this, The University of Leeds, with input from consortium members led in the conceptualisation of the ecosystem’s organisational design and conducted a literature review to understand the wider context of healthcare research ecosystems and what they entail. The Maastricht University Clinical Data Science lab (UNIMAAS) led on identifying the design principles and technology blueprints required for implementing a STRONG AYA technical infrastructure. UNIMAAS and UoL are working in close alignment with the EORTC to develop the Record of Processing Activity (ROPA) and Data Protection Impact Assessment (DPIA) for the consortium as a whole. Through consultation with WPLs and use of expertise, ECO has begun mapping stakeholders for another deliverable (D4.1) which will inform the evolution of the ecosystem as it matures. This deliverable also pulls on concepts articulated in the technical blueprint created for WP3 in the context of D3.1 (Data Management Plan) and D3.3 (development of architectural blueprint). The legal principles underpinning the ecosystem architecture are broadly articulated below and will be discussed in further detail in D2.2/D2.3 (STRONG AYA information governance and ethics framework/ethics guidelines). The discussion of sustainability is in its infancy and represents some initial thoughts that will be further developed including within deliverable D4.12 (to be provided in September 2025 (M36)). Protocol version 1.0 42 3. STRONG AYA Mission STRONG AYA’s mission is to improve healthcare services, research and outcomes for Adolescents and Young Adults (AYA) with cancer. As outlined in depth above, AYAs with cancer face age-specific issues (e.g. infertility, unemployment, financial problems) and decreased quality of life due to cancer and its treatment during a whole life of cancer survivorship. In addition, there are several challenges that AYAs present to traditional research and care. AYAs are a very complex group clinically, sociologically and demographically which makes using standardised protocols very difficult. Not only are they liminal, existing sociologically between childhood and mature adulthood, but they are also experiencing rapid social, personal and economic change. The model of care and treatment protocols used for AYAs will often depend on their local context and whether they are treated in paediatric, adult or integrated/comprehensive healthcare settings. A number of challenges limit efforts to improve care and establish interventions to improve AYA quality of life. The liminality of AYAs means there is a dearth of AYA dedicated trials, their greater mobility makes it difficult to enable travel for trial access and they are less likely to have financial stability that enables leaving work for trial participation. AYAs with cancer then require a new approach that can allow researchers and clinicians to access real world insights from a large population and has the agility not only to adapt to a heterogenous study population but also to varying healthcare systems. Our federated learning ecosystems will allow us to do both. To achieve our mission and to rectify the disparity in AYA care and research and to improve AYA outcomes across Europe, STRONG AYA is guided by the following principles: 1) Healthcare should be value-based STRONG AYA seeks to use data-driven insights as a starting level of evidence to drive rapid developments in research, care and policy. AYA cancer is considered ‘rare’ in oncology with an incidence rate of less than 6 per 100,000 persons per year. This means that clinical experience is diluted and (for example) AYA cancer is more likely to be suspected later and diagnose at advanced stage. There are specific difficulties in conducting clinical trials for AYAs as well.15 For the studies that do exist, numbers of subjects are unavoidably small, making statistically significant findings difficult and therefore it is unclear what are the potentially actionable insights to improve healthcare. By broadening the research using novel privacy-safe approaches towards data sharing and data analytics, STRONG AYA will bring novel insights into AYA healthcare, encourage ethical re-use for scarce AYA research data , provide real-world evidence to all important AYA oncology decision-makers, and thus, increasing the benefit for patients whilst making care more efficient. 2) Access to and experience of healthcare should be consistent and transparent across Europe As AYAs are an under-researched demographic and straddle the traditional divisions between paediatric and adult oncology, the type of or approach to care an AYA person experiences varies significantly between paediatric and adult oncological institutions, between regions, and between countries. By establishing a Core Outcome Set for AYA care and using data-driven insights gathered via our pan-European ecosystem, STRONG AYA will share insights with policy15 See for example, Ferrari et al (2021), Adolescents and young adults (AYA) with cancer: a position paper from the AYA Working Group of the European Society for Medical Oncology (ESMO) and the European Society for Paediatric Oncology (SIOPE). ESMO open, 6(2), 100096. https://doi.org/10.1016/j.esmoop.2021.100096; and Fern et al ((2014). Available, accessible, aware, appropriate, and acceptable: a strategy to improve participation of teenagers and young adults in cancer trials. The Lancet. Oncology, 15(8), e341–e350. https://doi.org/10.1016/S1470-2045(14)70113-5. Protocol version 1.0 43 makers to address and reduce inequalities across the entire disease pathway of different cancers in AYAs in different regions in Europe with an aim towards establishing a European-wide standard of care. STRONG AYA will enable AYA healthcare quality outcomes monitoring by tracking access to AYA nurse specialists, fertility consultants, and social workers for discussion about work and establish benchmarking between the different countries on key performance indicators. 3) Co-creation with stakeholders, especially patients Clinical trials and medical research historically have been driven by the questions and concerns clinicians and researchers wish to investigate. However, it is patients who are directly impacted by the outcomes of research. Their questions and concerns should be placed on equal footing with clinical research areas of interest. By involving patients in the process of co-creation, STRONG AYA will create a platform that serves patients and empowers them. STRONG AYA will equip AYAs with cancer with the data to better optimise their healthcare, and support shared and personalised decision-making between AYA and health care providers. This also extends to the control of, access to, and use of AYA’s data in the context of research and healthcare. 4) Control over data The key enabling technologies in STRONG AYA will revolve around patients and data-gathering institutions (such as clinical registries and treating hospitals) being able to retain the task of control over their data. Asking patients and institutions to hand over their data to a centralized European repository significantly increases the “trust distance” between the person giving the data and the steward guarding the data, in effect eroding the extent of direct controllership held by the data contributor. STRONG AYA implements a federated pan-European data access infrastructure while allowing data contributors, such as treating institutions and patient organizations, to retain direct controllership over their own data. This keeps the data private and protected against being used by anyone outside of the controlling institution. Federated integration of multi-institutional data retains local governance and control over data. The innovation we implement within STRONG AYA is to derive data-driven healthcare insights from multiple sets of private and geographically fragmented datasets; partners UNIMAAS and IKNL in the consortium are specialist experts in this question of “federated learning” which numerous successful projects on their track record. 5) FAIR and Federated data: sharing insight with compliance STRONG AYA follows the FAIR data management principles which means that data remains findable, accessible, interoperable, and reusable even while it stays fully private under the direct control of disparate institutions. The FAIR principles will accordingly be applied at partner, national and pan-European levels for data, and subsequently digital artefacts (e.g., software, publications, reports) generated from the project work. STRONG AYA will utilize federated analytics, i.e. the performance of statistical analyses and summary visualisations of data but without transmitting any individual patient-level data outside of the data-owning institution. STRONG-AYA also supports federated learning such that prognostic and predictive (statistical) models can be developed without exchanging individual patient-level data. Privacy protection for federated analytics and federated learning is based on the unfeasibility of reverse-engineering a particular individual subject’s identity from summaries, statistical models and other aggregated Protocol version 1.0 44 results (which are typically presented for reports and publications). This means that STRONG AYA partners and stakeholders will be ethically, technically and pragmatically empowered to share insights but not the actual data. This allows STRONG AYA to generate new insights from aggregated data to achieve its aims, in a way that complies with national and European standards of privacy, ethics and data security. 6) Sustainable scalability: offer new opportunities without leaving anyone behind The development of a COS for AYAs with cancer can enable STRONG AYA to offer new opportunities for the collection of prospective data that some of our participating centres have never collected before supporting new research and care innovation. Federated learning marks a new frontier in using data to solve modern health challenges. Federated learning is an agile and adaptable model that allows us to flexibly incorporate existing systems and practices into a larger ecosystem of knowledge exchange. A guiding principle of the STRONG AYA ecosystems is to accommodate local centres and their contexts whilst connecting them across Europe. Our ecosystems are ways of working that aim:  To generate a stronger culture of successful and sustainable working together about AYA with cancer  To integrate ‘traditional’ clinical, epidemiological and data science processes with patientcentred data, patients and their groups, policy makers and others  To speed up key analyses of data about AYA with cancer  To improve services, experiences, and outcomes Our ecosystems include:  Sophisticated websites  A set of local databases, set up in a very specific way  Portals through which stakeholders will enter and access information  Tools that we design and manage access to, that can optimise the knowledge gained from our local data  Expertise required to operate the ecosystem at both the European (expert guidance) and local (clinical support, data management, and technical/IT support) The COS and the federated infrastructure both allow STRONG AYA to scale and therefore increase its sustainable potential. 4. Governance Principles, Data Security and Ethics 4.1 General Governance - GDPR The in-depth development of the governance principles of STRONG AYA will be completed in the first year of the project. An inventory of relevant existing ethical and governance codes and guidelines already present in the various partner institutions will result in the development of the project’s ethical and legal guidelines and framework and will align principles from the different STRONG AYA partners as well as relevant EU governance and ethics principles, such as the ‘European Ethical Principles for Digital Health’ (2022) and key principles for data protection as laid out in the GDPR. These principles include (but are not limited to):  Lawfulness, fairness and transparency: [data shall be] processed lawfully, fairly and in a transparent manner in relation to the data subject); Protocol version 1.0 45  Purpose limitation: [data shall be] collected for specified, explicit and legitimate purposes and not further processed in a manner that is incompatible with those purposes; further processing for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes shall, in accordance with Article 89(1), not be considered to be incompatible with the initial purposes;  Data minimisation: [data shall be] adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed;  Accuracy: [data shall be] accurate and, where necessary, kept up to date; every reasonable step must be taken to ensure that personal data that are inaccurate, having regard to the purposes for which they are processed, are erased or rectified without delay;  Storage limitation: [data shall be] kept in a form which permits identification of data subjects for no longer than is necessary for the purposes for which the personal data are processed; personal data may be stored for longer periods insofar as the personal data will be processed solely for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) subject to implementation of the appropriate technical and organisational measures required by this Regulation in order to safeguard the rights and freedoms of the data subject;  Integrity and confidentiality: [data shall be] processed in a manner that ensures appropriate security of the personal data, including protection against unauthorised or unlawful processing and against accidental loss, destruction or damage, using appropriate technical or organisational measures;  Accountability: The controller shall be responsible for, and be able to demonstrate compliance with, paragraph 1 [the previous 6 principles]). Whilst it is premature at the time of writing (Spring 2023) to fully elaborate on each of these principles, we can expand upon some practical governance principles around data access and use in the ecosystems. The STRONG AYA governance principles chiefly concern how the STRONG AYA consortium defines what it will do with data and what it cannot do with data ethically and legally. They address this at two geographical levels: the local (usually national) ecosystems and a single pan-European ecosystem. 4.2. Data protection principles and governance 1) Local data ownership and stewardship At the pan-European level, a fundamental principle is that STRONG AYA will not take or distribute any consortium member’s data nor act as its steward. Each institution is the steward of its own data and therefore must use existing safeguards and comply with local regulations and procedures to ensure the security of data held on their own machines. 2) Pseudonymisation and compliance review The data that STRONG AYA partners will make privately accessible in a federated way will be pseudonymised, and the COS variables will be reviewed by data security experts to ensure that the desired COS variables are at the absolute minimum necessary to get the actionable insights that the consortium wants to achieve and not superfluous to that overall objective, according to data minimization principle (art.. 5.1.c of the GDPR). Ethical governance of STRONG AYA data protection activities will take place through an interplay of national governance procedures (related to the five countries involved in this project), local (institutional) governance procedures and project-level governance centralized in the Strong AYA Protocol version 1.0 52  Serves multiple stakeholders  enables a virtual desktop linkage, having access to parts of local IT systems  The highest layer will be public – anyone finding the website can see this layer – our purpose, our achievements, our openly published reports, summaries of services we offer to others  The next layer might be accessible to all Strong-AYA members, upon login. It might include internal policy drafts, for example, and ‘Apps’  Another layer might be only available through a specific new request – for example an industry partner, researcher, or policy-maker wanting to commission a new analysis  Further layers may include progressively more restricted information, as far as we want, and we are comfortable within our information security rules and systems 2. a set of databases at the local level (Data lake-houses) that:  will store individual-patient data in a private box, or ‘safe space’ within our local systems  will exist only according to the local regulations that we routinely use already, or that we develop locally during Strong-AYA  will restrict access to local team members according to their permissions (unless [e.g. in one nation] permissions are given or have been given to share at a local level) 3. Portals through which stakeholders will all be able to:  Enter information and data (that they ‘own’ ethically and legally and are permitted to enter)  View information and data to monitor, evaluate and compare outcomes (at a level of detail that fits with their permissions)  See relevant data summaries whether for clinical, research, service user or policy purposes, according to their permissions  Re-use already existing institutional infrastructure and data warehouses to the maximum extent possible 4. Tools that can optimise the knowledge gained by us and others from our work  By running predefined analyses automatically (‘in real time’, ‘on demand’, ‘on the fly’) upon our data  By building AYA-specific aspects, into (for example):  Utilising existing epidemiological questions (EuroCare)  Utilising existing patient-driven questions (their websites)  Utilising existing policy questions (ECO) The STRONG AYA ecosystems are also made up of individuals with expertise and/or roles. Some of these roles may be held by the same or multiple members within or without the STRONG AYA consortium at a given time. These include: 1. Data providers  Storer  Developer  Aggregator  Harmonizer  Publisher Protocol version 1.0 53  Register  Data maintainer 2. Policies, laws and rules parties  Policy makers  Standardised and regulation parties 3. Keystone actors  Founder 4. Service providers  Data-as-a-service providers  Analytics-as-a-service-providers  Data service developer 5. Reuser  Open data-driven organization  Application developer  Interpreter 6. Data intermediaries  Data brokers  Enablers  Integrators  Data extractor and transformer  Data analyzer  Data visualizer 7. Data user/data consumer  Data curator  Infrastructure provider  Data sponsor  Data consultant From a practical operation perspective, the individual capabilities and experts in STRONG AYA are bifurcated at the European and local/national level. At the European level, experts guide the building and maintenance of the ecosystems, including its technical requirements (UNIMAAS, UOL), its legal and ethical frameworks (EORTC) and what data the ecosystems will be collecting and analysing (SOUTHAMPTON). At local level, operational experts are needed to ensure the ecosystems function. These include data collectors in the form of researchers, clinicians, and clinical support staff such as research nurses; Local legal and ethical experts to ensure compliance with local regulations such as DPOs and internal ethics review boards; data managers to manage the data lake houses and ensure the data is FAIR and accurate; and finally data scientists or IT technicians to maintain the functionality of the technical infrastructure. Our culture should build a network between us, which can improve our patients’ cancer outcomes. This will include:  Working this way routinely, and finding it useful (even rewarding, or enjoyable) Protocol version 1.0 54  Ways to generate co-operation and connections, inter-dependence and creativity, which bring data science, clinical care, clinical research, epidemiology and service users closer together  Ways to hold data that ensure it is clean, integrates, can be packaged, analysed, learned from and applied  Better use and re-use of our data to generate information and expertise within and out-with Strong-AYA, rather than only moving knowledge forward in a traditional, linear manner  Provider – toprocessor - toanalyst – to – knowledge – to – policy; We will seek to reverse, change or re-order that sequence  Ways to work together, soon and for decades to come, when using our suitable information, data and analytical results appropriately for the data and the user 7. Sustainability – initial thoughts The sustainability of the STRONG AYA project is embedded in its way of working. Unlike traditional clinical trials, STRONG AYA is fundamentally about the development of new processes and networks to enable scientific discovery. Whilst sustainability factors for the project will be explored in greater depth in deliverables produced by WP4, it is useful here to sketch out some initial thoughts on how sustainability is can be built into the STRONG AYA ecosystems. Some areas of consideration are more mature at this point than others, and this report will be updated to reflect evolving sustainability concerns as the project matures. The first consideration is the software infrastructure sustainability. By partnering with the IKNL, the developer of the vantage6 software that operates the STRONG AYA technical infrastructure, we have a direct link to the technical operation and maturation of the software over time within the consortium itself. Moreover, the federated analytics and federated learning codes that will be built to operate STRONG AYA will be built on top of the IKNL infrastructure will be fully open source code and fully open access, given by UNIMAAS in a public software repository. The agility and adaptation offered by the federated learning infrastructure and the approach to ways of working in STRONG AYA mean that scaling STRONG AYA technologically is straightforward and can account for the diversity of EHRs and data processes of new member institutions. STRONG AYA is imagined to operate as a not for profit business, which means sustainability costs will be centred around expanding access to its analytics and new data lake-houses and maintaining the data managers required to ensure the technical infrastructure continues to operate after the end of the project. Given the wide range of stakeholders, this could involve a subscription service for research centres, regulatory bodies, NGOs, governments or policy makers who use STRONG AYA insights regularly, or payment by analysis or by view for more bespoke or ad-hoc use of the STRONG AYA analytics. A greater challenge will be negotiating STRONG AYA’s sustainability from a governance perspective; both with onboarding new participants and for governing the project at the end of the funding period. While it is too early yet to consider the organizational governance structure after funding, the EORTC’s expansive European knowledge and establishment of best practices from the onset of the project, coupled with the successful connection of STRONG AYA’s already diverse consortium will provide persuasive use-cases that will, it is hoped, assuage data security concerns and contribute positively to the European Digital Health Space agenda. Furthermore, other members of the STRONG AYA consortium are involved in other European projects tackling similar concerns, such as the JANE Protocol version 1.0 55 project led by the Instituto Nazionale dei Tumori, offering STRONG AYA expertise and the opportunity to synergise with other European projects. 8. Conclusion/ next steps This document summarises key components of the ecosystem business architecture for STRONG AYA. The development of the ecosystems’ infrastructure is ongoing and as such, this document represents the alignment achieved thus far on the governance and technical aspects of the ecosystem and the consortium’s progress to date. It should therefore be treated as a ‘living document’, capturing the work done to the point of submission and concepts agreed upon amongst the consortium thus far. It is anticipated that these structures will refine and evolve over the course of the project. The STRONG AYA ecosystem business architecture outlines the initial design of the national and panEuropean ecosystems and the principles that underpin them. It complements the technical infrastructure of the STRONG AYA network by setting out the ecosystem’s organisational structure. The document summarises the mission and objectives of the project and governance principles; the legal structure and considerations required to implement the ecosystems, an abridgement of the data management and technical blueprint, the organisational structure of the ecosystems and briefly touches upon areas of further consideration for the sustainability of the ecosystems beyond the funding period (sustainability planning is part of other deliverables of the project). It is supplementary to other deliverables of the project. The management of data is more exhaustively defined in the first Data Management Plan (D3.1, already submitted at time of writing in M6) with a final version due at the end of the project. The technical requirements are discussed in further depth in the evolving technical blue print (D3.3 – due M12). The governance and ethics framework is being developed in D2.2 (expected M12). The operational plans of the ecosystems, both local/national and pan-European, are deliverables 4.4, 4.6, 4.7 (due M9 and M12). Sustainability planning is the focus of D4.12 (M36), and D4.15 (54). will continue throughout the life of the project.