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BackgroundThe status of the data-driven management of cancer care as well as the challenges, opportunities, and recommendations aimed at accelerating the rate of progress in this field are topics of great interest. Two international workshops, one conducted in June 2019 in Cordoba, Spain, and one in October 2019 in Athens, Greece, were organized by four Horizon 2020 (H2020) European Union (EU)–funded projects: BOUNCE, CATCH ITN, DESIREE, and MyPal. The issues covered included patient engagement, knowledge and data-driven decision support systems, patient journey, rehabilitation, personalized diagnosis, trust, assessment of guidelines, and interoperability of information and communication technology (ICT) platforms. A series of recommendations was provided as the complex landscape of data-driven technical innovation in cancer care was portrayed. ObjectiveThis study aims to provide information on the current state of the art of technology and data-driven innovations for the management of cancer care through the work of four EU H2020–funded projects. MethodsTwo international workshops on ICT in the management of cancer care were held, and several topics were identified through discussion among the participants. A focus group was formulated after the second workshop, in which the status of technological and data-driven cancer management as well as the challenges, opportunities, and recommendations in this area were collected and analyzed. ResultsTechnical and data-driven innovations provide promising tools for the management of cancer care. However, several challenges must be successfully addressed, such as patient engagement, interoperability of ICT-based systems, knowledge management, and trust. This paper analyzes these challenges, which can be opportunities for further research and practical implementation and can provide practical recommendations for future work. ConclusionsTechnology and data-driven innovations are becoming an integral part of cancer care management. In this process, specific challenges need to be addressed, such as increasing trust and engaging the whole stakeholder ecosystem, to fully benefit from these innovations.

BackgroundLong-term side-effects associated with different prostate cancer treatment approaches are common. Sexual challenges are the most frequently occurring issues and can result in increased psychological morbidity. It is recognized that barriers to communication can make initiating discussions around sexual concerns in routine practice difficult. Health care professionals need to routinely initiate conversations, effectively engage with patients, and assess needs in order to provide essential support. One proposed method that could support health care professionals to do this involves the use of prompts or structured frameworks to guide conversations. ObjectiveThis study aimed to assess feasibility, acceptability, and satisfaction with the tablet-based Engagement, Assessment, Support, and Sign-posting (EASSi) tool designed to facilitate and structure sexual well-being discussions in routine prostate cancer care. MethodsHealth care professionals (n=8) used the EASSi tool during 89 posttreatment appointments. Quantitative data were recorded based on program usage and surveys completed by health care professionals and patients. Qualitative data exploring perceptions on use of the tool were gathered using semistructured interviews with all health care professionals (n=8) and a sample of patients (n=10). ResultsSurveys were completed by health care professionals immediately following each appointment (n=89, 100%). Postal surveys were returned by 59 patients (66%). Health care professionals and patients reported that the tool helped facilitate discussions (81/89, 91% and 50/59, 85%, respectively) and that information provided was relevant (82/89, 92% and 50/59, 85%, respectively). The mean conversation duration was 6.01 minutes (SD 2.91). Qualitative synthesis identified the tool’s ability to initiate and structure discussions, improve the “depth” of conversations, and normalize sexual concerns. ConclusionsThe EASSi tool was appropriate and acceptable for use in practice and provided a flexible approach to facilitate routine brief conversations and deliver essential sexual well-being support. Further work will be conducted to evaluate the effectiveness of using the tablet-based tool in prostate cancer care settings.

BackgroundPatients with malignant pleural mesothelioma (MPM) have a life-limiting illness and short prognosis and experience many debilitating symptoms from early in the illness. Innovations such as remote symptom monitoring are needed to enable patients to maintain wellbeing and manage symptoms in a proactive and timely manner. The Advanced Symptom Management System (ASyMS) has been successfully used to monitor symptoms associated with cancer. ObjectiveThis study aimed to determine the feasibility and acceptability of using an ASyMS adapted for use by patients with MPM, called ASyMSmeso, enabling the remote monitoring of symptoms using a smartphone. MethodsThis was a convergent mixed methods study using patient-reported outcome measures (PROMs) at key time points over a period of 2-3 months with 18 patients. The Sheffield Profile for Assessment and Referral for Care (SPARC), Technology Acceptance Model (TAM) measure for eHealth, and Lung Cancer Symptom Scale-Mesothelioma (LCSS-Meso) were the PROMs used in the study. Patients were also asked to complete a daily symptom questionnaire on a smartphone throughout the study. At the end of the study, semistructured interviews with 11 health professionals, 8 patients, and 3 carers were conducted to collect their experience with using ASyMSmeso. ResultsEighteen patients with MPM agreed to participate in the study (33.3% response rate). The completion rates of study PROMs were high (97.2%-100%), and completion rates of the daily symptom questionnaire were also high, at 88.5%. There were no significant changes in quality of life, as measured by LCSS-Meso. There were statistically significant improvements in the SPARC psychological need domain (P=.049) and in the “Usefulness” domain of the TAM (P=.022). End-of-study interviews identified that both patients and clinicians found the system quick and easy to use. For patients, in particular, the system provided reassurance about symptom experience and the feeling of being listened to. The clinicians largely viewed the system as feasible and acceptable, and areas that were mentioned included the early management of symptoms and connectivity between patients and clinicians, leading to enhanced communication. ConclusionsThis study demonstrates that remote monitoring and management of symptoms of people with MPM using a mobile phone are feasible and acceptable. The evidence supports future trials using remote symptom monitoring to support patients with MPM at home.

BackgroundPatients with lung cancer (LC) report lower quality of life (QoL) and higher levels of psychological distress compared with other cancer populations. Lung cancer stigma (LCS) may in part explain these findings.AimWe investigated the prevalence of patient-perceived lung cancer stigma (LCS) and its relationships to symptom burden/severity, depression, and deficits in health-related quality of life (HR-QoL).MethodsIn this descriptive, observational, and cross-sectional study, 201 participants were sent questionnaires. These included the Cataldo Lung Cancer Stigma Scale (CLCSS), the Lung Cancer Symptom Scale, the Centre for Epidemiologic Studies-Depression Scale, and the Quality of Life Inventory.ResultsParticipants were on average 69 years old, 52% women, 95% ever smokers, and 18.5% current smokers. The mean total CLCSS score was 53.1 (SD = 14.1; range = 31-94). LCS was significantly correlated with younger age (P

Oncology patients undergoing cancer treatment experience an average of fifteen unrelieved symptoms that are highly variable in both their severity and distress. Recent advances in Network Analysis (NA) provide a novel approach to gain insights into the complex nature of co-occurring symptoms and symptom clusters and identify core symptoms. We present findings from the first study that used NA to examine the relationships among 38 common symptoms in a large sample of oncology patients undergoing chemotherapy. Using two different models of Pairwise Markov Random Fields (PMRF), we examined the nature and structure of interactions for three different dimensions of patients' symptom experience (i.e., occurrence, severity, distress). Findings from this study provide the first direct evidence that the connections between and among symptoms differ depending on the symptom dimension used to create the network. Based on an evaluation of the centrality indices, nausea appears to be a structurally important node in all three networks. Our findings can be used to guide the development of symptom management interventions based on the identification of core symptoms and symptom clusters within a network.

ContextRisk profiling of oncology patients based on their symptom experience assists clinicians to provide more personalized symptom management interventions. Recent findings suggest that oncology patients with distinct symptom profiles can be identified using a variety of analytic methods.ObjectivesThe objective of this study was to evaluate the concordance between the number and types of subgroups of patients with distinct symptom profiles using latent class analysis and K-modes analysis.MethodsUsing data on the occurrence of 25 symptoms from the Memorial Symptom Assessment Scale, that 1329 patients completed prior to their next dose of chemotherapy (CTX), Cohen's kappa coefficient was used to evaluate for concordance between the two analytic methods. For both latent class analysis and K-modes, differences among the subgroups in demographic, clinical, and symptom characteristics, as well as quality of life outcomes were determined using parametric and nonparametric statistics.ResultsUsing both analytic methods, four subgroups of patients with distinct symptom profiles were identified (i.e., all low, moderate physical and lower psychological, moderate physical and higher Psychological, and all high). The percent agreement between the two methods was 75.32%, which suggests a moderate level of agreement. In both analyses, patients in the all high group were significantly younger and had a higher comorbidity profile, worse Memorial Symptom Assessment Scale subscale scores, and poorer QOL outcomes.ConclusionBoth analytic methods can be used to identify subgroups of oncology patients with distinct symptom profiles. Additional research is needed to determine which analytic methods and which dimension of the symptom experience provide the most sensitive and specific risk profiles.

Effective symptom management is a critical component of cancer treatment. Computational tools that predict the course and severity of these symptoms have the potential to assist oncology clinicians to personalize the patient's treatment regimen more efficiently and provide more aggressive and timely interventions. Three common and inter-related symptoms in cancer patients are depression, anxiety, and sleep disturbance. In this paper, we elaborate on the efficiency of Support Vector Regression (SVR) and Non-linear Canonical Correlation Analysis by Neural Networks (n-CCA) to predict the severity of the aforementioned symptoms between two different time points during a cycle of chemotherapy (CTX). Our results demonstrate that these two methods produced equivalent results for all three symptoms. These types of predictive models can be used to identify high risk patients, educate patients about their symptom experience, and improve the timing of pre-emptive and personalized symptom management interventions.

IntroductionWhile some evidence exists that real-time remote symptom monitoring devices can decrease morbidity and prevent unplanned admissions in oncology patients, overall, these studies have significant methodological weaknesses. The electronic Symptom Management using the Advanced Symptom Management System (ASyMS) Remote Technology (eSMART) study is designed to specifically address these weaknesses with an appropriately powered, repeated-measures, parallel-group stratified randomised controlled trial of oncology patients.Methods and analysisA total of 1108 patients scheduled to commence first-line chemotherapy (CTX) for breast, colorectal or haematological cancer will be recruited from multiple sites across five European countries.Patients will be randomised (1:1) to the ASyMS intervention (intervention group) or to standard care currently available at each site (control group). Patients in the control and intervention groups will complete a demographic and clinical questionnaire, as well as a set of valid and reliable electronic patient-reported outcome measures at enrolment, after each of their CTX cycles (up to a maximum of six cycles) and at 3, 6, 9 and 12 months after completion of their sixth cycle of CTX. Outcomes that will be assessed include symptom burden (primary outcome), quality of life, supportive care needs, anxiety, self-care self-efficacy, work limitations and cost effectiveness and, from a health professional perspective, changes in clinical practice (secondary outcomes).Ethics and disseminationEthical approval will be obtained prior to the implementation of all major study amendments. Applications will be submitted to all of the ethics committees that granted initial approval.eSMART received approval from the relevant ethics committees at all of the clinical sites across the five participating countries. In collaboration with the European Cancer Patient Coalition (ECPC), the trial results will be disseminated through publications in scientific journals, presentations at international conferences, and postings on the eSMART website and other relevant clinician and consumer websites; establishment of an eSMART website (www.esmartproject.eu) with publicly accessible general information; creation of an eSMART Twitter Handle, and production of a toolkit for implementing/utilising the ASyMS technology in a variety of clinical practices and other transferable health care contexts.Trial registration numberNCT02356081.

Objective: Digital health tools are increasingly being recognised as effective interventions in monitoring chronic health conditions. This systematic review addressed how digital health is currently utilised in patients with head and neck cancer as an adjunct to care. Method: Studies of the development or evaluation of an eHealth, telemedicine or telemonitoring tool were eligible. A narrative synthesis was performed as per Preferred Reporting Items for Systematic Review and Meta-Analyses reporting guidelines. Results: Twenty-nine studies of digital health tools in head and neck cancer were identified. Nine were randomised, controlled trials but most had concern of bias. Fourteen (48 per cent) of the interventions used multiple modes of delivery. The primary digital tool functions are symptom tracking and self-care, prehabilitation and rehabilitation, psychological support, and education, including decision aids. Most tools aimed to support patients during active cancer treatment. Conclusion: There are a small number of digital health tools for head and neck cancer patients; however, there is a lack of well-designed randomised, controlled trials to demonstrate effectiveness. [ABSTRACT FROM AUTHOR]