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Background: The increased number of cancer survivors and the recognition of physical and psychosocial challenges, present from cancer diagnosis through active treatment and beyond, led to the discipline of cancer survivorship. Design and methods: Herein, we reflected on the different components of survivorship care, existing models and priorities, in order to facilitate the promotion of high-quality European survivorship care and research. Results: We identified five main components of survivorship care: (i) physical effects of cancer and chronic medical conditions; (ii) psychological effects of cancer; (iii) social, work and financial effects of cancer; (iv) surveillance for recurrences and second cancers; and (v) cancer prevention and overall health and well-being promotion. Survivorship care can be delivered by structured care models including but not limited to shared models integrating primary care and oncology services. The choice of the care model to be implemented has to be adapted to local realities. High-quality care should be expedited by the generation of: (i) focused and shared European recommendations, (ii) creation of tools to facilitate implementation of coordinated care and (iii) survivorship educational programs for health care teams and patients. The research agenda should be defined with the participation of health care providers, researchers, policy makers, patients and caregivers. The following patient-centered survivorship research areas were highlighted: (i) generation of a big data platform to collect long-term real-world data in survivors and healthy controls to (a) understand the resources, needs and preferences of patients with cancer, and (b) understand biological determinants of survivorship issues, and (ii) develop innovative effective interventions focused on the main components of survivorship care. Conclusions: The European Society for Medical Oncology (ESMO) can actively contribute in the efforts of the oncology community toward (a

Background: The increased number of cancer survivors and the recognition of physical and psychosocial challenges, present from cancer diagnosis through active treatment and beyond, led to the discipline of cancer survivorship. Design and methods: Herein, we reflected on the different components of survivorship care, existing models and priorities, in order to facilitate the promotion of high-quality European survivorship care and research. Results: We identified five main components of survivorship care: (i) physical effects of cancer and chronic medical conditions; (ii) psychological effects of cancer; (iii) social, work and financial effects of cancer; (iv) surveillance for recurrences and second cancers; and (v) cancer prevention and overall health and well-being promotion. Survivorship care can be delivered by structured care models including but not limited to shared models integrating primary care and oncology services. The choice of the care model to be implemented has to be adapted to local realities. High-quality care should be expedited by the generation of: (i) focused and shared European recommendations, (ii) creation of tools to facilitate implementation of coordinated care and (iii) survivorship educational programs for health care teams and patients. The research agenda should be defined with the participation of health care providers, researchers, policy makers, patients and caregivers. The following patient-centered survivorship research areas were highlighted: (i) generation of a big data platform to collect long-term real-world data in survivors and healthy controls to (a) understand the resources, needs and preferences of patients with cancer, and (b) understand biological determinants of survivorship issues, and (ii) develop innovative effective interventions focused on the main components of survivorship care. Conclusions: The European Society for Medical Oncology (ESMO) can actively contribute in the efforts of the oncology community toward

01 februari 2020, Contains fulltext : 220990.pdf (Publisher’s version ) (Closed access), PURPOSE: Fatigue is a common and potentially disabling symptom in patients with cancer. It can often be effectively reduced by exercise. Yet, effects of exercise interventions might differ across subgroups. We conducted a meta-analysis using individual patient data of randomized controlled trials (RCT) to investigate moderators of exercise intervention effects on cancer-related fatigue. METHODS: We used individual patient data from 31 exercise RCT worldwide, representing 4366 patients, of whom 3846 had complete fatigue data. We performed a one-step individual patient data meta-analysis, using linear mixed-effect models to analyze the effects of exercise interventions on fatigue (z score) and to identify demographic, clinical, intervention- and exercise-related moderators. Models were adjusted for baseline fatigue and included a random intercept on study level to account for clustering of patients within studies. We identified potential moderators by testing their interaction with group allocation, using a likelihood ratio test. RESULTS: Exercise interventions had statistically significant beneficial effects on fatigue (beta = -0.17; 95% confidence interval [CI], -0.22 to -0.12). There was no evidence of moderation by demographic or clinical characteristics. Supervised exercise interventions had significantly larger effects on fatigue than unsupervised exercise interventions (betadifference = -0.18; 95% CI -0.28 to -0.08). Supervised interventions with a duration

Contains fulltext : 203302.pdf (publisher's version ) (Open Access), The case for cancer prevention in Europe is the same as for all other parts of the world. The number of cancers is increasing, driven by demographic change and evolution in the exposure to risk factors, while the cost of treating patients is likewise spiralling. Estimations suggest that around 40% of cancers in Europe could be prevented if current understanding of risk and protective factors was translated into effective primary prevention, with further reductions in cancer incidence and mortality by screening, other approaches to early detection, and potentially medical prevention. However, the infrastructure for cancer prevention tends to be fragmented between and within different countries in Europe. This lack of a coordinated approach recently led to the foundation of Cancer Prevention Europe (Forman et al., 2018), a collaborative network with the main aims of strengthening cancer prevention in Europe by increasing awareness of the needs, the associated required resources and reducing inequalities in access to cancer prevention across Europe. This article showcases the need for strengthening cancer prevention and introduces the objectives of Cancer Prevention Europe and its foreseen future role in reducing the European cancer burden.

Objectives: To evaluate the effects of exercise interventions on sleep disturbances and sleep quality in patients with mixed cancer diagnoses, and identify demographic, clinical, and intervention-related moderators of these effects. Methods: Individual patient data (IPD) and aggregated meta-analyses of randomized controlled trials (RCTs). Using data from the Predicting OptimaL cAncer RehabIlitation and Supportive care project, IPD of 2173 adults (mean age = 54.8) with cancer from 17 RCTs were analyzed. A complementary systematic search was conducted (until November 2018) to study the overall effects and test the representativeness of analyzed IPD. Effect sizes of exercise effects on self-reported sleep outcomes were calculated for all included RCTs. Linear mixed-effect models were used to evaluate the effects of exercise on post-intervention outcome values, adjusting for baseline values. Moderator effects were studied by testing interactions for demographic, clinical and intervention-related characteristics. Results: For all 27 eligible RCTs from the updated search, exercise interventions significantly decreased sleep disturbances in adults with cancer (g = −0.09, 95% CI [−0.16; −0.02]). No significant effect was obtained for sleep quality. RCTs included in IPD analyses constituted a representative sample of the published literature. The intervention effects on sleep disturbances were not significantly moderated by any demographic, clinical, or intervention-related factor, nor by sleep disturbances. Conclusions: This meta-analysis provides some evidence that, compared to control conditions, exercise interventions may improve sleep disturbances, but not sleep quality, in cancer patients, although this effect is of a small magnitude. Among the investigated variables, none was found to significantly moderate the effect of exercise interventions on sleep disturbances.

Item does not contain fulltext, Background: Exercise effects in cancer patients often appear modest, possibly because interventions rarely target patients most in need. This study investigated the moderator effects of baseline values on the exercise outcomes of fatigue, aerobic fitness, muscle strength, quality of life (QoL), and self-reported physical function (PF) in cancer patients during and post-treatment. Methods: Individual patient data from 34 randomized exercise trials (n = 4519) were pooled. Linear mixed-effect models were used to study moderator effects of baseline values on exercise intervention outcomes and to determine whether these moderator effects differed by intervention timing (during vs post-treatment). All statistical tests were two-sided. Results: Moderator effects of baseline fatigue and PF were consistent across intervention timing, with greater effects in patients with worse fatigue (Pinteraction = .05) and worse PF (Pinteraction = .003). Moderator effects of baseline aerobic fitness, muscle strength, and QoL differed by intervention timing. During treatment, effects on aerobic fitness were greater for patients with better baseline aerobic fitness (Pinteraction = .002). Post-treatment, effects on upper (Pinteraction < .001) and lower (Pinteraction = .01) body muscle strength and QoL (Pinteraction < .001) were greater in patients with worse baseline values. Conclusion: Although exercise should be encouraged for most cancer patients during and post-treatments, targeting specific subgroups may be especially beneficial and cost effective. For fatigue and PF, interventions during and post-treatment should target patients with high fatigue and low PF. During treatment, patients experience benefit for muscle strength and QoL regardless of baseline values; however, only patients with low baseline values benefit post-treatment. For aerobic fitness, patients with low baseline values do not appear to benefit from exercise during treatment.

Contains fulltext : 170325.pdf (Publisher’s version ) (Open Access), This individual patient data meta-analysis aimed to evaluate the effects of exercise on quality of life (QoL) and physical function (PF) in patients with cancer, and to identify moderator effects of demographic (age, sex, marital status, education), clinical (body mass index, cancer type, presence of metastasis), intervention-related (intervention timing, delivery mode and duration, and type of control group), and exercise-related (exercise frequency, intensity, type, time) characteristics. Relevant published and unpublished studies were identified in September 2012 via PubMed, EMBASE, PsycINFO, and CINAHL, reference checking and personal communications. Principle investigators of all 69 eligible trials were requested to share IPD from their study. IPD from 34 randomised controlled trials (n=4519 patients) that evaluated the effects of exercise compared to a usual care, wait-list or attention control group on QoL and PF in adult patients with cancer were retrieved and pooled. Linear mixed-effect models were used to evaluate the effects of the exercise on post-intervention outcome values (z-score) adjusting for baseline values. Moderator effects were studies by testing interactions. Exercise significantly improved QoL (beta=0.15, 95%CI=0.10;0.20) and PF (beta=0.18, 95%CI=0.13;0.23). The effects were not moderated by demographic, clinical or exercise characteristics. Effects on QoL (betadifference_in_effect=0.13, 95%CI=0.03;0.22) and PF (betadifference_in_effect=0.10, 95%CI=0.01;0.20) were significantly larger for supervised than unsupervised interventions. In conclusion, exercise, and particularly supervised exercise, effectively improves QoL and PF in patients with cancer with different demographic and clinical characteristics during and following treatment. Although effect sizes are small, there is consistent empirical evidence to support implementation of exercise as part of cancer care.