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Abstract
Introduction Immunotherapies, such as immune checkpoint inhibitors and chimeric antigen receptor T-cell therapy, have significantly improved the clinical outcomes of various malignancies. However, they also cause immune-related adverse events (irAEs) that can be challenging to predict, prevent and treat. Although they likely interact with health-related quality of life (HRQoL), most existing evidence on this topic has come from clinical trials with eligibility criteria that may not accurately reflect real-world settings. The QUALITOP project will study HRQoL in relation to irAEs and its determinants in a real-world study of patients treated with immunotherapy.
Methods and analysis This international, observational, multicentre study takes place in France, the Netherlands, Portugal and Spain. We aim to include about 1800 adult patients with cancer treated with immunotherapy in a specifically recruited prospective cohort, and to additionally obtain data from historical real-world databases (ie, databiobanks) and medical administrative registries (ie, national cancer registries) in which relevant data regarding other adult patients with cancer treated with immunotherapy has already been stored. In the prospective cohort, clinical health status, HRQoL and psychosocial well-being will be monitored until 18 months after treatment initiation through questionnaires (at baseline and 3, 6, 12 and 18 months thereafter), and by data extraction from electronic patient files. Using advanced statistical methods, including causal inference methods, artificial intelligence algorithms and simulation modelling, we will use data from the QUALITOP cohort to improve the understanding of the complex relationships among treatment regimens, patient characteristics, irAEs and HRQoL.
Ethics and dissemination All aspects of the QUALITOP project will be conducted in accordance with the Declaration of Helsinki and with ethical approval from a suitable local ethics committee, and all patients will provide signed informed consent. In addition to standard dissemination efforts in the scientific literature, the data and outcomes will contribute to a smart digital platform and medical data lake. These will (1) help increase knowledge about the impact of immunotherapy, (2) facilitate improved interactions between patients, clinicians and the general population and (3) contribute to personalised medicine.
Trial registration number NCT05626764.
- Adverse events
- ONCOLOGY
- Epidemiology
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Strengths and limitations of this study
The ‘monitoring multidimensional aspects of QUAlity of Life after cancer ImmunoTherapy, an Open smart digital Platform for personalised prevention and patient management’ (QUALITOP) project will create an international, multicentre, real-world cohort that aggregates data of multiple types and from multiple sources.
The collected data will contribute to a medical data lake underlying a smart digital platform, which may be used by various stakeholders.
Despite its potential benefits, the QUALITOP project relies on data from heterogeneous patient groups and from partly validated patient questionnaires.
As this project started during the COVID-19 pandemic, we expect to limit recruitment shortage by study extension and enrichment of historical databases with retrospective data.
Introduction
Cancer immunotherapy has revolutionised oncology care over the last two decades, adding to the existing therapeutic arsenal through its unique action in stimulating the immune system to recognise and attack cancer cells.1 Two subtypes of immune intervention that have gained particular interest, namely immune checkpoint inhibitors (ICIs) and chimeric antigen receptor T cells (CAR T cells), have hugely different mechanisms of action, indications and adverse events. Moreover, we lack long-term data on their health effects due to their relative novelty. International registries that monitor patient well-being in real-life settings provide invaluable opportunities to fill such knowledge gaps.
Immunotherapies trigger unique toxicities by activating the immune system to attack healthy cells. These immune-related adverse events (irAEs) occur in up to 96% of patients who receive ICIs, with severe irAEs reported in 10%–28% of patients receiving ICI monotherapy (Common Terminology Criteria for Adverse Events, grade ≥3)2–5 and 59% of patients receiving combination therapy.5 Dermatological, gastrointestinal and endocrine irAEs are most common, and management varies from symptomatic treatment for mild (grade 1–2) irAEs to corticosteroid or immunosuppressant (eg, infliximab) treatment, or even permanent immunotherapy cessation, for life-threatening (grade 4) irAEs.6 Nevertheless, toxicity profiles after ICI therapy appear more favourable than those of chemotherapy, with lower risks of developing any AEs or severe AEs (grade ≥3) for immunotherapy.7 CAR T-cell therapy also causes various treatment-specific irAEs, with cytokine release syndrome, immune effector cell-associated neurotoxicity syndrome, infection and cytopenia the most common and severe in the acute phase (<28 days after CAR T-cell infusion).8 Although irAEs can be life-threatening, they are usually reversible with early intervention. The most common long-term side effects are ongoing cytopenias, impaired immune reconstitution with B-cell aplasia, T-cell depletion and hypogammaglobulinemia with increased risk of infection.9
Besides improved clinical outcomes, immunotherapy should offer the patient psychosocial benefits compared with conventional therapies. To this end, trials have reported smaller impairments in health-related quality of life (HRQoL), longer times to HRQoL deterioration and better control of cancer symptoms.10 11 However, immunotherapies and their associated irAEs may still affect HRQoL given that we know little of their associated late-onset and long-lasting effects.12 Moreover, although Immunotherapy has clear and proven benefits over conventional anticancer treatments,10 11 13–19 this evidence has predominantly come from clinical trials that have strict eligibility criteria. These data may exclude patients with poor performance status (Eastern Cooperative Oncology Group, performance status >1), concomitant cancers, autoimmune diseases or long-term systemic corticosteroid use.3 20 Therefore, we do not know if the clinical and psychosocial benefits of immunotherapy in trial settings apply to real-world cohorts. The growth in survivor populations as these treatments elicit durable clinical responses and long-term remission for malignancies that previously had poor prognoses21 emphasises the need for research into the long-term well-being and HRQoL of patients treated with these therapies.
We aim to study the multidimensional aspects of patients’ HRQoL, the irAEs that develop during ICI and CAR T-cell therapy, and the relevant determinants of both, using a purpose-built smart digital platform with a medical data lake. This digital platform will improve data provision to various stakeholders about risk profiles for irAE development or HRQoL deterioration. In this way, we can improve personalised and shared decision-making for future patients eligible for immunotherapy.
Methods and analysis
Study design
The ‘Monitoring multidimensional aspects of QUAlity of Life after cancer ImmunoTherapy, an Open smart digital Platform for personalised prevention and patient management’ (QUALITOP) project is an international, multicentre, real-world, observational cohort study. We will provide insights into the medical and psychosocial determinants of quality of life after cancer immunotherapy, making use of big data analyses, artificial intelligence (AI) and simulation modelling, before integrating the results in an information technology platform developed for the project. Additional information can be found on the project’s website.22 This study is registered at ClinicalTrials.gov under identifier NCT05626764.
We will study adverse events and quality of life among patients with cancer during and after immunotherapy. The QUALITOP cohort will combine a historical cohort of existing patients and a prospective cohort enrolled specifically for this project (figure 1). The historical cohort will comprise patient data routinely collected in existing databases and medical registries in Spain, France, Portugal and the Netherlands, for which existing informed consent allows the reuse of data within the context of this European collaboration. For the prospective cohort, patients will be recruited in the same countries under the coordination of Hospital Clinic de Barcelona (IDIBAPS), Hospices Civils de Lyon, Instituto Português de Oncologia Lisboa, and Amsterdam University Medical Centers and University Medical Center Groningen, respectively. Figure 2 shows the study timeline. Note that patients will not be included in both the historic and prospective cohorts.
Structure of the ‘monitoring multidimensional aspects of QUAlity of Life after cancer ImmunoTherapy, an Open smart digital Platform for personalised prevention and patient management’ (QUALITOP) project.
Timeline of patient monitoring in the historic and prospective cohorts of the ‘monitoring multidimensional aspects of QUAlity of Life after cancer ImmunoTherapy, an Open smart digital Platform for personalised prevention and patient management’ (QUALITOP) project.
Patient selection
Patients will be eligible for inclusion in a cohort if they are aged ≥18 years at the time of signing informed consent and have an oncological diagnosis either treated or to be treated with ICIs or CAR T cells (as monotherapy or in combination with other anticancer treatments). Patients treated as part of a clinical trial may also be included if permitted by the clinical trial. However, we will exclude patients who are pregnant, under guardianship or who refuse to sign informed consent. For the prospective cohort, patients can be recruited from the decision for immunotherapy until their second cycle of immunotherapy. Patients receiving CAR T-cell therapy will be recruited from after leucapheresis to the start of lymphodepleting chemotherapy, before CAR T-cell infusion. For the prospective cohort, patients will be asked to participate by trained members of the medical staff, such as doctors and (research) nurses, during visits that are part of regular care. Based on the average number of eligible patients treated in the participating clinical centres, we aim to include about 1800 patients in the prospective cohort.
Study outcomes
The primary outcome of the QUALITOP study is HRQoL, combining the patient’s perspective of their physical, psychological and social functioning.23 We will measure this outcome repeatedly in the prospective cohort and obtain data for a selection of patients and time points in the historic cohort. The secondary outcome of the QUALITOP study is the incidence and severity of irAEs, which we will extract from the electronic records for patients in both cohorts.
Data collection
Overview of data sources and timeline
Patient data for both the historic and prospective cohorts will come from existing and new databases at sites in France, the Netherlands, Portugal and Spain, as summarised in table 1 and detailed in online supplemental file 1. Each study site has different specialisations and will cover different oncological diagnoses and therapies.
Supplemental material
Overview of data sources and their population characteristics per country
Figure 2 shows the proposed timeline of patient monitoring in the historic and prospective cohorts. Data for eligible patients from the historic cohorts were collected between 2016 and 2021, while patient inclusion for the prospective cohorts was initiated in April 2021 and will continue until January 2023. Afterwards, inclusion is intended to be continued in a sustainability programme. We will monitor patients closely for the first 6 months of treatment or until cessation, after which patients will enter a phase of less intensive monitoring until 18 months after treatment initiation or the QUALITOP project ends (figure 2). Clinical data will be manually extracted from electronic patient files for both cohorts. The QUALITOP Questionnaire, which aims to collect data from various psychosocial domains, will only be used in the prospective cohort.
Data collection in the prospective cohort
Except in France, data from the prospective arm of the cohort are being collected and managed in Research Electronic Data Capture (REDCap), hosted by the participating institutions.24 25 REDCap is a secure, web-based platform designed to support data capture for research studies. It provides the following: (1) an intuitive interface for validated data capture; (2) audit trails for tracking data manipulation and export procedures; (3) automated export procedures for seamless data downloads to common statistical packages; and (4) procedures for data integration and interoperability with external sources. In France, data collection is being managed in Easily, a web-based electronic health record platform developed locally and hosted at Hospices Civils de Lyon. The database structure fits the common set of covariates in QUALITOP.
Clinical data
Clinical data will be manually extracted from electronic patient files for each routine visit in the first 6 months of treatment and at fixed time points in the following year (9, 12 and 18 months). The timing of routine visits will differ by treatment type (ICI or CAR T-cell). We will assess medical history, medication use, prior anticancer treatments and cancer characteristics at the initiation of immunotherapy. Both at baseline and during follow-up, we will collect data from physical examinations (ie, weight, performance status, blood pressure), laboratory assessments (ie, C reactive protein, neutrophils, leucocytes) and related to irAEs according to the Common Terminology Criteria for Adverse Events, V.5, of the National Cancer Institute.26 Data about treatment for irAEs will be collected according to BioPortal’s Drug Ontology,27 available in REDCap. We will evaluate treatment response using the Response Evaluation Criteria in Solid Tumors (RECIST)28 and the Lugano criteria for lymphomas.29 Examples of data collected within the domains specified above can be found in online supplemental file 2.
Psychosocial questionnaires
We developed psychosocial questionnaires to assess the multiple dimensions of quality of life and its potential psychosocial determinants in patients, necessary for the minimal data set of each patient included in the prospective cohort. A more in-depth questionnaire is issued at baseline and a shorter version is issued during follow-up at 3, 6, 12 and 18 months. We also modified the questionnaire slightly for patients receiving CAR T-cell therapy. Table 2 summarises the domains included in each version of the questionnaire. The questionnaire as a whole was not pretested (because it was constructed during the COVID-19 pandemic, and it was not possible to meet with patients). However, it was reviewed by oncologists in all the countries involved in the data collection.
QUALITOP Questionnaire domains at baseline and during follow-up
The flowchart in figure 3 illustrates the hypothesised framework for the interrelatedness of the questionnaire domains and their association with quality of life. We created French, English, Portuguese, Spanish and Dutch versions of the questionnaires, and when no validated translation existed, an external service provider specialising in academic and medical translation completed the translation. A researcher in each country also proofread the questionnaires, ensuring that the English version was consistent with his/her language.
Framework for the medical and psychosocial determinants of quality of life.
The first part of the questionnaire, issued at baseline, characterises the population based on sociodemographic and psychosocial factors. Subsequently, the questionnaire includes assessments of quality of life, anxiety, depression, (in)tolerance of uncertainty, social support, health literacy, medication-related beliefs and behaviours, relationship with their main physician and expectations of immunotherapy. The follow-up questionnaires will track longitudinal changes in these aspects. Patients will be invited to signal any change in their personal situation every time they take the questionnaire (eg, patient stopped smoking, patient is now divorced, a new family member diagnosed with cancer) and will be asked to complete the rest of the questionnaire at each assessment. We will assess these features using ad hoc items and established questionnaires.
Ad hoc items explore various features in the QUALITOP Questionnaire. Ad hoc items are used for domains for which no suitable validated questions/questionnaires were available. The items are based on expert opinions and prior experience with research in similar patient populations. Especially for domains 5 (‘medication and treatment’) and 6 (‘opinions on cancer treatment and care’), clinicians’ knowledge and experience with immunotherapy treatment was of key importance in developing and evaluating the ad hoc items.
First, ad hoc items explore sociodemographic data (eg, sex, age, number of children, marital status), gender roles (eg, health responsibilities in a relationship), health habits (eg, smoking, drinking, physical activity) and family history of cancer (eg, number of family members who have or have had cancer, whether patients underwent genetic testing for cancer). Second, they explore the four main dimensions of social support30 (material, informational, emotional, esteem) and how patients feel that they are available and provided by their partners (if applicable), family members and friends/loved ones. Third, they explore medication-related beliefs and behaviours, including physical discomfort, medication use, number of doctors usually consulted outside cancer care, self-medication, complementary care (eg, physiotherapist, psychologist) and perception of so-called ‘natural’ medicines and practices. Finally, they explore opinions about cancer treatment and care, adapting items from the Treatment Representations Inventory31 to immunotherapy for the doctor–patient relationship, perception of the level of information provided and expected side effects or outcomes.
The Functional Assessment of Cancer Therapy—General (FACT-G),32 suitable for patients with any tumour type, will assess quality of life. This validated questionnaire has been widely used for this purpose since the nineties.33 34 The FACT-Lym, which includes 15 additional tailored questions, will then be used for patients with lymphoma.35 We will use the authorised Dutch, French, Portuguese and Spanish versions of each questionnaire.
The validated Dutch, French, Portuguese and Spanish versions of the Hospital Anxiety and Depression Scale will be used to assess anxiety and depression longitudinally.36–39 We aim to observe indicators of deterioration in quality of life and/or a response shift phenomenon (ie, adaptation and adjustment to the disease that allows quality of life to remain equivalent despite the illness).40–43
Immunotherapy remains an innovative treatment associated with uncertain treatment outcomes and side effects. Therefore, we will use the short version of the Intolerance of Uncertainty Scale (IUS Short Form) to assess possible difficulties with the management of uncertain situations.44
Health literacy, referring to the ability of individuals to access, understand, assess and use information and services for health, will be assessed using the Single-Item Literacy Screener (SILS). This has been validated in French and Spanish45 46 and translated to Portuguese and Dutch. The SILS aims to measure participants' functional literacy; that is, their ability to understand information that might be necessary for their health.
Data collection in the historic cohort
For the historic databases, we aim to collect the same clinical data collected for patients in the prospective cohort. For patient-reported psychosocial data, inclusion will depend on its availability in each existing database. Table 3 summarises the known data availability in the different historic databases, by domain, for the baseline and follow-up data.
Data availability for historic databases
Data analysis plan
Data harmonisation and handling of missing data
To enable analyses with the data from the historical and/or prospective QUALITOP cohorts, we must first harmonise the generated data. Separate analyses may be required for the historical datasets given their heterogeneous structures. Although the structure of data to be collected for the prospective cohort has been harmonised beforehand, differences in patient populations, treatments and legislations between the five participating centres mean that differences will exist. Where these differences result in missing data, we will handle missingness separately for each analysis after careful consideration of the mechanism, paying close attention to associations between missingness, outcomes and exposures.47 The method used will also depend on the nature of the statistical analysis, such as multiple imputation for regression-based methods48 and the missing indicator approach for machine learning algorithms.49 To capture heterogeneity between participating centres, we will include a centre effect in all the analyses as either fixed or random effects.50
Statistical analyses
We plan to use a broad variety of statistical methods for the purposes of description (eg, describe baseline characteristics), explanation (eg, explain changes in HRQoL by irAEs) and prediction (eg, predict patients at risk for HRQoL deterioration through patient characteristics). In addition, we will use machine learning techniques and mapping methods to exploit fully the vast amount of collected data and provide a deep understanding of the causal mechanisms underlying HRQoL of patients treated with immunotherapy. A special focus lies on understanding the influence of adverse events and individual characteristics.
The observational nature of the data will require specific methodologies. We will use tools developed in the framework of the potential outcomes,51 such as inverse probability of treatment weighting,52 doubly robust estimators53 and targeted maximum likelihood estimation,54 to account for confounding. Directed acyclic graphs,55 informed by clinical frameworks like that depicted in figure 3, will be developed in collaboration with partners to inform variable selection. These methods will help us to determine the causal effect of irAEs on HRQoL components. Intermediate analyses will be performed to identify the prognostic factors associated with irAEs, and boosting methods56 will be used to determine those factors and their appropriate functional forms. The historical datasets will inform this step.
To further address the relationships between irAEs and HRQoL, we will use mediation analysis to disentangle the direct effect of individual characteristics and treatment on HRQoL, considering the effect mediated by irAEs.57 This should uncover the factors driving HRQoL and could subsequently inform personalised care to maximise HRQoL. This stage will use machine learning algorithms, such as random forests,58 to develop a prediction model for future HRQoL based on current demographic, psychosocial and clinical information.
The data collected in the QUALITOP project will benefit from repeated assessments of HRQoL over 18 months, facilitating the study of both individual trajectories over time and the causes and timing of changes in HRQoL. We will use mixed effect models and item response models to analyse the repeated measurements,59 while simultaneously considering joint modelling to account for death as a competing event.60
We will then combine the outputs of the disparate analyses to develop a causal loop diagram to illustrate the complex web of medical and psychosocial factors affecting quality of life.61 This diagram will inform the development and validation of a quantitative simulation model, using a system dynamics method to understand HRQoL after cancer immunotherapy under different hypothetical public health scenarios.
Medical data lake and smart digital platform
The QUALITOP project also aims to develop data management principles in a smart digital platform and associated medical data lake (figure 4) that will enable networked medical agencies to share and exchange trusted and secure medical data with automated and robust controls based on Findable, Accessible, Interoperable, Reusable principles.62 The digital platform will use the medical, psychological and psychosocial data collected in the historic and prospective QUALITOP cohorts. By employing monitoring technologies and advanced data analytics, the data lake and smart digital platform will allow for the determination of predictive markers in subpopulations associated with irAE development and HRQoL impairment. We will use data-driven automation, prediction and decision support analytics with technologies such as AI to make predictions and recommendations for a given set of operator-defined objectives. By leveraging modern analytics and data management capabilities and working with AI methods such as machine learning to improve the HRQoL of patients undergoing immunotherapy and to minimise the risks of relapse, healthcare organisations can transform existing networks into smart digital healthcare ecosystems.
Simplified representation of the architecture of the smart data platform and its underlying medical data lake.
Patient monitoring using the smart digital platform
Finally, the smart digital platform aims to allow not only collaborative, integrated and personalised case monitoring but also actionable treatment adjustments or recommendations. These benefits will help reinforce treatment planning and improve the effectiveness of actions designed to reduce treatment effects, making room for the necessary corrective actions at different stages. Data from the historic Immucare database will be used to develop and test the clustering algorithms that will be integrated in the smart digital platform and used to simplify the data, look for patterns and similarities, and ultimately contribute to personalised patient monitoring.
Patient and public involvement
As ‘experts by experience’, patient representatives play a central role in reporting data on treatment outcomes, making their involvement key to the success of this project. Involvement will be facilitated by embedding the QUALITOP project in the European Cancer Patients Coalition as a health research project on big data and personalised medicine. This will provide invaluable opportunities to gain input and advice from patients and their relatives. In addition, the QUALITOP project can be followed on Twitter, through a regular dedicated newsletter and through online events for patients with cancer. In the online meetings, researchers and partners of QUALITOP project can give a comprehensive overview of the project and how it can improve the quality of life of patients. At the same time, patients with cancer will have the opportunity to express their concerns, describe their experiences and give valuable feedback regarding the project. Thus, we offer various routes for proactive and reactive patient involvement to ensure that the research meets the needs and wishes of patients and their families. More detail about these routes to patient and public involvement can be found at the following links:
European Cancer Patients Coalition: https://ecpc.org/health-and-research/qualitop/.
Twitter: @h2020qualitop.
QUALITOP news and event: https://h2020qualitop.liris.cnrs.fr/wordpress/index.php/.
QUALITOP LinkedIn: https://www.linkedin.com/company/qualitop-h2020/.
Ethics and dissemination
Ethical considerations
The QUALITOP project will be conducted according to the Declaration of Helsinki. The local ethics committees of all participating centres have granted ethical approval (Personal protection committee Hospices Civils de Lyon, Medical Ethics Committee University Medical Center Groningen, Medical Ethics Committee Amsterdam University Medical Centers, Ethics Committee for Health Instituto Português de Oncologia Lisboa, Ethics Committee Hospital Clinic of Barcelona). Patients will be invited to participate by their treating physician and will be required to provide signed informed consent. For the historic cohort, data from existing study databases and medical administrative registries will only be used if patients had provided signed informed consent that allowed the reuse of data for (international) scientific purposes. For analyses or dissemination activities at both national and international level, data will be protected under the European General Data Protection Regulation. The smart data platform and data lake will ensure privacy under the Security Rule of the Health Insurance Portability and Accountability Act. Moreover, the data lake will only include aggregated data, further ensuring anonymity.
Dissemination
Continuing from the strong patient and public involvement throughout the earlier stages of the study, we will ensure that our results are not only presented at patient organisation meetings but also distributed through national and social media. Furthermore, professional engagement will be stimulated by presenting the study results at national and international conferences and by submitting manuscripts to peer-reviewed scientific journals. All results will be reported following current standards (eg, Strengthening the Reporting of Observational Studies in Epidemiology guidelines).63 The final product of the QUALITOP project, the smart digital platform, will also play a central role in the dissemination of information to various stakeholders, underpinned by a big medical data lake of aggregated data from the project’s various data sources. This platform will use secured portals that are accessible to each major stakeholder group and will include functions and information tailored to their specific needs (table 4).
Specific outcomes expected by key stakeholder group
Discussion
The QUALITOP project aims to develop and implement a digital immunotherapy platform in Europe. It will use big data analysis, AI and simulation modelling approaches to collect and aggregate real-world HRQoL data, monitor patients’ health statuses, conduct causal inference analyses, create harm-reduction recommendations for patients and other stakeholders, and disseminate findings efficiently and effectively. The planned data analyses should expand scientific knowledge about the complex interplay between clinical factors, psychosocial factors and long-term quality of life in a real-life setting after immunotherapy. Beyond this, we plan to use the acquired data and knowledge to nourish a smart digital platform that should offer a host of benefits to various stakeholders. Of course, we anticipate challenges on the path to achieving these outcomes. For example, the COVID-19 pandemic has already affected patient inclusion in the QUALITOP cohorts. We hope to resolve this with the received 6-month extension from the European Union, as well as efforts to retrospectively enrich the historical databases that are part of QUALITOP. Potential effects on treatment regimens and HRQoL may need to be considered in the statistical analyses. We also anticipate regulatory challenges for the smart digital platform, but by respecting the strict European regulations that exist to ensure patient privacy, we expect to deliver this with little difficulty. The QUALITOP project will expand knowledge about the health statuses and quality of life of patients after treatment with either ICI or CAR T cells in real-world settings, delivering a smart digital platform that can empower patients with cancer and inform healthcare providers. We hope that this project will illustrate that, by making use of smart digital solutions, international collaborations can accelerate the acquisition and dissemination of scientific knowledge surrounding cancer treatment.
Ethics statements
Patient consent for publication
Acknowledgments
Doctored (www.doctored.org.uk) provided manuscript editing services for the final drafts.
References
Supplementary materials
Supplementary Data
This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.
Footnotes
Twitter @susana_puig
PCV and MC contributed equally.
Contributors PV, MC, GHdB, CL, AMS, SD, MGdS, AFE, AR, MP, MSJ, AE, MP, M-SH, CR, M-JK, MGHvO, ES-Z, AM, EC, AA, MP, MF, EC, SP and DM-B have contributed to the conception and design of this study protocol. PV, MC, GHdB, SP and DM-B drafted the manuscript. PV, MC, GHdB, CL, AMS, SD, MGdS, AFE, AR, MP, MSJ, AE, MP, M-SH, CR, M-JK, MGHvO, ES-Z, AM, EC, AA, MP, MF, EC, SP and DM-B have offered critical revision of the manuscript for important intellectual content. PCV, MC, GHdB, CL, AMS, SD, MGdS, AFE, AR, MP, MSJ, AE, MP, M-SH, CR, M-JK, MGHvO, ES-Z, AM, EC, AA, MP, MF, EC, SP and DM-B have read and approved the final manuscript.
Funding This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement Nº 875171. Additionally, the UK Medical Research Council is supporting CL (Skills Development Fellowship, MR/T032448/1). The funding sources did not play a role in the design of the study, collection of data or writing of this protocol.
Competing interests M-JK: honoraria from Kite, a Gilead Company, Novartis and Miltenyi Biotec, Roche, and Bristol Myers Squibb/Celgene; consultancy or advisory role for Kite, a Gilead Company, Roche, Novartis, Bristol Myers Squibb/Celgene and Miltenyi Biotec; research funding from Kite, a Gilead Company, Roche, Takeda and Celgene; and travel support from Kite, a Gilead Company, Roche, Novartis and Miltenyi Biotec. All other authors declare that they have no competing interests.
Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.