Risultati per: Uso dei test del DNA tumorale circolante per i pazienti con cancro

Background
Social networks are an important, although overlooked, component of community-based health promotion. Advances in social network research have highlighted different social network intervention (SNI) strategies to improve community-based health promotion. The aim of this project is to collaborate with community and policy stakeholders to explore how to best apply these SNI strategies to improve the resilience, health and well-being of adults in Amsterdam, and more broadly in the Netherlands.

Methods and analysis
To this end, we will collaboratively develop an intervention planning tool called the ‘Health in All Networks Simulator (HANS)’. This tool will be capable of virtually testing different SNI strategies and forecasting their possible impact on resilience, health and well-being. Taking a mixed-methods approach consisting of a combination of interviews, group model building workshops and agent-based modelling with members of two communities in Amsterdam and policy stakeholders, we will foster a shared learning process while ensuring ownership and relevance of HANS to ongoing community-based health promotion practice.

Ethics and dissemination
The research project has been approved by the research ethics committee of Wageningen University (approval numbers: 2024-039; 2024-226). HANS will be shared directly with stakeholders. The results will be made available to the public via open-access publications and conferences.

Pancreatic cancer is considered the third deadliest cancer in the US, resulting in more than 50 000 deaths each year, partially because tumors of the pancreas often go undetected until later stages. Although early-stage and localized pancreatic cancer has a much higher survival rate, there are no reliable US Food and Drug Administration–approved screening methods to detect tumors before they spread to the lymph nodes or other organs.

Introduction
The provision of optimal care for older adults with complex chronic conditions (CCCs) poses significant challenges due to the interplay of multiple medical, pharmacological, functional and psychosocial factors. To address these challenges, the I-CARE4OLD project, funded by the EU-Horizon 2020 programme, developed an advanced clinical decision support tool—the iCARE tool—leveraging large longitudinal data from millions of home care and nursing home recipients across eight countries. The tool uses machine learning techniques applied to data from interRAI assessments, enriched with registry data, to predict health trajectories and evaluate pharmacological and non-pharmacological interventions. This study aims to pilot the iCARE tool and assess its feasibility, usability and impact on clinical decision-making among healthcare professionals.

Methods and analysis
A minimum of 20 participants from each of the seven countries (Italy, Belgium, the Netherlands, Poland, Finland, Czechia and the USA) participated in the study. Participants were general practitioners, geriatricians and other medical specialists, nurses, physiotherapists and other healthcare providers involved in the care of older adults with CCC. The study design involved pre-surveys and post-surveys, tool testing with hypothetical patient cases and evaluations of predictions and treatment recommendations. Two pilot modalities—decision loop and non-decision loop—were implemented to assess the effect of the iCARE tool on clinical decisions. Descriptive statistics and bivariate and multivariate analysis will be conducted. All notes and text field data will be translated into English, and a thematic analysis will be performed. The pilot testing started in September 2024, and data collection ended in January 2025. At the time this protocol was submitted for publication, data collection was complete but data analysis had not yet begun.

Ethics and dissemination
Ethical approvals were granted in each participating country before the start of the pilot. All participants gave informed consent to participate in the study. The results of the study will be published in peer-reviewed journals and disseminated during national and international scientific and professional conferences and meetings. Stakeholders will also be informed via the project website and social media, and through targeted methods such as webinars, factsheets and (feedback) workshops. The I-CARE4OLD consortium will strive to publish as much as possible open access, including analytical scripts. Databases will not become publicly available, but the data sets used and/or analysed as part of the project can be made available on reasonable request and with the permission of the I-CARE4OLD consortium.

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