Circulating pre-treatment Epstein-Barr virus DNA as prognostic factor in locally-advanced nasopharyngeal cancer in a non-endemic area.

The prognostic value of pre-treatment Epstein-Barr Virus (EBV) DNA viral load for non-endemic, locally-advanced, EBV-related nasopharyngeal cancer (NPC) patients is yet to be defined. All patients with EBV encoded RNA (EBER)-positive NPC treated at our Institution from 2005 to 2014 with chemotherapy (CT) concurrent with radiation (RT) +/- induction chemotherapy (ICT) were retrospectively reviewed. Pre-treatment baseline plasma EBV DNA (b-EBV DNA) viral load was detected and quantified by PCR. Median b-EBV DNA value was correlated to potential influencing factors by univariate analysis. Significant variables were then extrapolated and included in a multivariate linear regression model. The same variables, including b-EBV DNA, were correlated with Disease Free Survival (DFS) and Overall Survival (OS) by univariate and multivariate analysis.A total of 130 locally-advanced EBER positive NPC patients were evaluated. Overall, b-EBV DNA was detected in 103 patients (79.2%). Median viral load was 554 copies/mL (range 50-151075), and was positively correlated with T stage (p=0.002), N3a-b vs N0-1-2 stage (p=0.048), type of treatment (ICT followed by CTRT, p=0.006) and locoregional and/or distant disease recurrence (p=0.034). In the overall population, DFS and OS were significantly longer in patients with pre-treatment negative EBV DNA than in positive subjects at the multivariate analysis.Negative b-EBV DNA can be considered as prognostic biomarker of longer DFS and OS in NPC in non-endemic areas. This finding needs confirmation in larger prospective series, with standardized and inter-laboratory harmonized method of plasma EBV DNA quantification.

Personalized support for chronic conditions. A novel approach for enhancing self-management and improving lifestyle.

OBJECTIVE: Solutions for improving management of chronic conditions are under the attention of healthcare systems, due to the increasing prevalence caused by demographic change and better survival, and the relevant impact on healthcare expenditures. The objective of this study was to propose a comprehensive architecture of a mHealth system aimed at boosting the active and informed participation of patients in their care process, while at the same time overcoming the current technical and psychological/clinical issues highlighted by the existing literature. METHODS: After having studied the current challenges outlined in the literature, both in terms of technological and human requirements, we focused our attention on some specific psychological aspects with a view to providing patients with a comprehensive and personalized solution. Our approach has been reinforced through the results of a preliminary assessment we conducted on 22 patients with chronic conditions. The main goal of such an assessment was to provide a preliminary understanding of their needs in a real context, both in terms of self-awareness and of their predisposition toward the use of IT solutions. RESULTS: According to the specific needs and features, such as mindfulness and gamification, which were identified through the literature and the preliminary assessment, we designed a comprehensive open architecture able to provide a tailor-made solution linked to specific individuals' needs. CONCLUSION: The present study represents the preliminary step towards the development of a solution aimed at enhancing patients' actual perception and encouraging self-management and self-awareness for a better lifestyle. Future work regards further identification of pathology-related needs and requirements through focus groups including all stakeholders in order to describe the architecture and functionality in greater detail.

Domains of Health IT and Tailoring of Evaluation: Practicing Process Modeling for Multi-Stakeholder Benefits.

This contribution focuses on the heterogeneity and complexity of health information technology services and systems in a multi-stakeholder environment. We propose the perspective of process modeling as a method to break out complexity, represent heterogeneity, and provide tailored evaluation and optimization of health IT systems and services. Two case studies are presented to show how process modeling is needed to fully understand the information flow, thus identifying requirements and specifications for information system re-engineering and interoperability; detect process weaknesses thus designing corrective measures; define metrics as a mean to evaluate and ensure system quality; and optimize the use of resources.