Psychological distress and lower health-related quality of life are associated with need for dietary support among colorectal cancer survivors with overweight or obesity

Objective: Two-third of colorectal cancer (CRC) survivors are overweight or obese. Psychological distress and low health-related quality of life (HRQoL) may be barriers to improving diet. We aimed to assess associations between psychological distress and HRQoL and the need for dietary support in CRC survivors with overweight or obesity. Methods: All alive individuals diagnosed with CRC between 2000 and 2009, as registered by the Dutch population-based Eindhoven Cancer Registry, were eligible for participation and received a questionnaire. Multivariable logistic regression analyses were conducted to assess associations between HRQoL (EORTC QLQ-C30), symptoms of anxiety and depression (HADS), and self-reported need for dietary support (single-item). Results: A total of 1458 completed the questionnaire (response rate 82%), and 756 (43%) had a BMI of 25.0 or higher and complete data on “need for dietary support” and were included for analyses. BMI ranged between 25.0 and 60.6 (mean, 28.9; SD, 3.6). The majority (71.7%) was overweight (BMI ≥ 25), and 28.3% obese (BMI ≥ 30). Twenty-one percent reported a need for dietary support which was associated with more psychological distress and lower HRQoL. Those who experienced symptoms of anxiety or depression were more likely to report a need for dietary support (27.6% and 28.7%) than those who did not experience symptoms of anxiety (12.3%; OR 2.02; 95% CI 1.22–3.35) or depression (13.5%; OR 1.96; 95% CI 1.19–3.22). Conclusions: Results suggest that psychological distress and lower HRQoL should be taken into account while promoting a healthy diet in overweight or obese CRC survivors since these factors may hinder adherence to a healthy diet.</p

Low radiographic muscle density is associated with lower overall and disease-free survival in early-stage colorectal cancer patients

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Pre-to-post diagnosis weight trajectories in colorectal cancer patients with non-metastatic disease

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BOLD Vision 2020:Designing a vision for the future of Big Open Legal Data

The vision of openlaws.eu is to make access to justice easier for citizens, business- es and legal experts. For this purpose, an innovative legal information platform has been designed by the openlaws.eu project, considering the needs of various stakeholder groups as well as the latest developments in technology and our information society. Access to justice is a fundamental problem in the European Union. There are over 500 million citizens and over 21 million businesses who live, work and operate in 28 jurisdictions, written in 24 official languages. A common market cannot work without a legal system as a basis. Legal information is a public good and it is the duty of governments and the EU to inform citizens and business about the law. In a democracy and under the rule of law everybody should know legislation and case law – or at least have access to it. Legal tech is a new terms for new technology that can be applied to legal information in order to create better access and better understanding of the law. However, just because things can be done, does not mean automatically that they are done. Financial and organisational restrictions and the lack of competency can be a deal-breaker for innovation. Open data, open innovation and open source software can be a potential solution to this problem, especially when combined to one coherent ecosystem. openlaws.eu has developed a prototype platform upon these new open concepts. The application and implementation of some of the features of this innovative legal cloud service indicate where the road of “Big Open Legal Data” can lead us in the upcoming years. The project team envisages an environment, where a “social layer” is put on top of the existing “institutional layer”. Citizens, businesses and legal experts can actively collaborate on the basis of primary legislation and case law. Linked and aggregated legal data provide a solid basis. Such information can then be represented in traditional and more innovative ways. Text and data mining as well as legal intelligence help to process large amounts of legal information automatically, so that experts can focus on the more complicated questions. In the next five years more and more legal data will be opened up, not only because of the PSI Directive, but also because it is in the best interest of governments. As a result, we anticipate that more legal tech start-ups will emerge, as already happened during the past two years. They will apply innovative concepts and new technology on existing legal information and create better access to justice in the EU, in Member States and in the world

External validation and updating of prediction models for estimating the 1-year risk of low health-related quality of life in colorectal cancer survivors

Objectives Timely identification of colorectal cancer (CRC) survivors at risk of experiencing low health-related quality of life (HRQoL) in the near future is important for enabling appropriately tailored preventive actions. We previously developed and internally validated risk prediction models to estimate the 1-year risk of low HRQoL in long-term CRC survivors. In this article, we aim to externally validate and update these models in a population of short-term CRC survivors. Study Design and Setting In a pooled cohort of 1,596 CRC survivors, seven HRQoL domains (global QoL, cognitive/emotional/physical/role/social functioning, and fatigue) were measured prospectively at approximately 5 months postdiagnosis (baseline for prediction) and approximately 1 year later by a validated patient-reported outcome measure (European Organization for Research and Treatment of Cancer Quality of life Questionnaire–Core 30). For each HRQoL domain, 1-year scores were dichotomized into low vs. normal/high HRQoL. Performance of the previously developed multivariable logistic prediction models was evaluated (calibration and discrimination). Models were updated to create a more parsimonious predictor set for all HRQoL domains. Results Updated models showed good calibration and discrimination (AUC ≥0.75), containing a single set of 15 predictors, including nonmodifiable (age, sex, education, time since diagnosis, chemotherapy, radiotherapy, stoma, and comorbidities) and modifiable predictors (body mass index, physical activity, smoking, anxiety/depression, and baseline fatigue and HRQoL domain scores). Conclusion Externally validated and updated prediction models performed well for estimating the 1-year risk of low HRQoL in CRC survivors within 6 months postdiagnosis. The impact of implementing the models in oncology practice to improve HRQoL outcomes in CRC survivors needs to be evaluated