UCSF Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, San Francisco, California, USA.
Patient Stakeholder, University of California San Francisco, San Francisco, California, USA.
BMJ Open. 2024 Feb 24;14(2):e077432. doi: 10.1136/bmjopen-2023-077432.
Depression occurs in over 50% of individuals living with multiple sclerosis (MS) and can be treated using many modalities. Yet, it remains: under-reported by patients, under-ascertained by clinicians and under-treated. To enhance these three behaviours likely to promote evidence-based depression care, we engaged multiple stakeholders to iteratively design a first-in-kind digital health tool. The tool, MS CATCH (Care technology to Ascertain, Treat, and engage the Community to Heal depression in patients with MS), closes the communication loop between patients and clinicians. Between clinical visits, the tool queries patients monthly about mood symptoms, supports patient self-management and alerts clinicians to worsening mood via their electronic health record in-basket. Clinicians can also access an MS CATCH dashboard displaying patients' mood scores over the course of their disease, and providing comprehensive management tools (contributing factors, antidepressant pathway, resources in patient's neighbourhood). The goal of the current trial is to evaluate the clinical effect and usability of MS CATCH in a real-world clinical setting.
MS CATCH is a single-site, phase II randomised, delayed start, trial enrolling 125 adults with MS and mild to moderately severe depression. Arm 1 will receive MS CATCH for 12 months, and arm 2 will receive usual care for 6 months, then MS CATCH for 6 months. Clinicians will be randomised to avoid practice effects. The effectiveness analysis is superiority intent-to-treat comparing MS CATCH to usual care over 6 months (primary outcome: evidence of screening and treatment; secondary outcome: Hospital Anxiety Depression Scale-Depression scores). The usability of the intervention will also be evaluated (primary outcome: adoption; secondary outcomes: adherence, engagement, satisfaction).
University of California, San Francisco Institutional Review Board (22-36620). The findings of the study are planned to be shared through conferences and publishments in a peer-reviewed journal. The deidentified dataset will be shared with qualified collaborators on request, provision of CITI and other certifications, and data sharing agreement. We will share the results, once the data are complete and analysed, with the scientific community and patient/clinician participants through abstracts, presentations and manuscripts.
NCT05865405.
超过 50%的多发性硬化症 (MS) 患者会出现抑郁症状，可通过多种方式进行治疗。然而，这种情况仍然存在：患者报告不足、临床医生发现不足、治疗不足。为了增强这三种行为，可能会促进基于证据的抑郁护理，我们让多个利益相关者共同参与，逐步设计了一种首创的数字健康工具。该工具名为 MS CATCH（用于确定、治疗和吸引社区治愈多发性硬化症患者抑郁的护理技术），它可以弥合患者和临床医生之间的沟通障碍。在就诊之间，该工具每月询问患者情绪症状，支持患者自我管理，并通过他们的电子健康记录收件箱提醒临床医生情绪恶化。临床医生还可以访问 MS CATCH 仪表板，查看患者在疾病过程中的情绪得分，并提供全面的管理工具（促成因素、抗抑郁药途径、患者所在社区的资源）。目前试验的目的是评估 MS CATCH 在真实临床环境中的临床效果和可用性。
MS CATCH 是一项单站点、二期、随机、延迟启动试验，招募了 125 名患有 MS 和轻度至中度严重抑郁的成年人。第 1 组将接受 12 个月的 MS CATCH，第 2 组将先接受 6 个月的常规护理，然后再接受 6 个月的 MS CATCH。临床医生将随机分组，以避免实践效果。有效性分析是基于意图的治疗优势，将 MS CATCH 与 6 个月的常规护理进行比较（主要结局：筛查和治疗证据；次要结局：医院焦虑抑郁量表-抑郁评分）。还将评估干预措施的可用性（主要结局：采用；次要结局：依从性、参与度、满意度）。
加州大学旧金山分校机构审查委员会（22-36620）。该研究的结果计划通过会议和同行评审期刊上的出版物进行分享。请求提供 CITI 和其他认证以及数据共享协议后，将与合格的合作者共享去识别数据集。一旦数据完成并分析，我们将通过摘要、演讲和手稿与科学界和患者/临床参与者分享结果。
NCT05865405。
