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首页> 外文期刊>BMC Medical Informatics and Decision Making >Patients-centered SurvivorShIp care plan after Cancer treatments based on Big Data and Artificial Intelligence technologies (PERSIST): a multicenter study protocol to evaluate efficacy of digital tools supporting cancer survivors
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Patients-centered SurvivorShIp care plan after Cancer treatments based on Big Data and Artificial Intelligence technologies (PERSIST): a multicenter study protocol to evaluate efficacy of digital tools supporting cancer survivors

机译：基于大数据和人工智能技术的癌症治疗患者为中心的生存计划（持续）：多中心研究协议，以评估支持癌症幸存者的数字工具的疗效

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It is encouraging to see a substantial increase in individuals surviving cancer. Even more so since most of them will have a positive effect on society by returning to work. However, many cancer survivors have unmet needs, especially when it comes to improving their quality of life (QoL). Only few survivors are able to meet all of the recommendations regarding well-being and there is a body of evidence that cancer survivors’ needs often remain neglected from health policy and national cancer control plans. This increases the impact of inequalities in cancer care and adds a dangerous component to it. The inequalities affect the individual survivor, their career, along with their relatives and society as a whole. The current study will evaluate the impact of the use of big data analytics and artificial intelligence on the self-efficacy of participants following intervention supported by digital tools. The secondary endpoints include evaluation of the impact of patient trajectories (from retrospective data) and patient gathered health data on prediction and improved intervention against possible secondary disease or negative outcomes (e.g. late toxicities, fatal events). The study is designed as a single-case experimental prospective study where each individual serves as its own control group with basal measurements obtained at the recruitment and subsequent measurements performed every 6?months during follow ups. The measurement will involve CASE-cancer, Patient Activation Measure and System Usability Scale. The study will involve 160 survivors (80 survivors of Breast Cancer and 80 survivors of Colorectal Cancer) from four countries, Belgium, Latvia, Slovenia, and Spain. The intervention will be implemented via a digital tool (mHealthApplication), collecting objective biomarkers (vital signs) and subjective biomarkers (PROs) with the support of a (embodied) conversational agent. Additionally, the Clinical Decision Support system (CDSS), including visualization of cohorts and trajectories will enable oncologists to personalize treatment for an efficient care plan and follow-up management. We expect that cancer survivors will significantly increase their self-efficacy following the personalized intervention supported by the m-HealthApplication compared to control measurements at recruitment. We expect to observe improvement in healthy habits, disease self-management and self-perceived QoL. Trial registration ISRCTN97617326. https://doi.org/10.1186/ISRCTN97617326 . Original Registration Date: 26/03/2021.
机译：令人鼓舞的是，在患有癌症中幸存的人的大量增加。更重要的是，因为大多数人将通过回归工作对社会产生积极影响。然而，许多癌症幸存者都有未满足的需求，特别是在提高他们的生活质量（QOL）时。只有少数幸存者能够满足有关福祉的所有建议，并且存在一系列证据表明癌症幸存者的需求往往忽视卫生政策和国家癌症控制计划。这增加了癌症护理中不等式的影响，并为其添加了危险组件。不平等影响个人幸存者，他们的职业生涯以及整个亲戚和社会。目前的研究将评估利用大数据分析和人工智能对数字工具支持的干预后参与者的自我效能的影响。辅助端点包括评估患者轨迹的影响（从回顾性数据）和患者收集了对预测的健康数据和改善了可能的继发性疾病或负面结果的干预（例如，晚期毒性，致命事件）。该研究设计为单一的实验前瞻性研究，其中每个人用作自己的对照组，在招生和随后进行的基础测量和随后进行每6个月的测量。测量将涉及患者癌症，患者激活测量和系统可用规模。该研究将涉及来自四个国家，比利时，拉脱维亚，斯洛文尼亚和西班牙的160名幸存者（乳腺癌和80名乳腺癌患者的乳腺癌和80次幸存者）。干预将通过数字工具（MHHELELEALACIPPLICACT）来实施，以（体现）对话剂的支持，收集目标生物标志物（生命体征）和主观生物标志物（专业人士）。此外，临床决策支持系统（CDS），包括群组和轨迹的可视化将使诱导员个性化进行高效护理计划和后续管理的处理。我们预计癌症幸存者将在M-HealthApplication支持的个性化干预后显着提高其自我效能，与在招聘中的对照测量结果相比。我们希望观察健康习惯，疾病自我管理和自我感知QoL的改善。试用登记ISRCTN97617326。 https://doi.org/10.1186/isrctn97617326。原始注册日期：26/03/2021。

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