Olmert Tony, Cooper Jason D, Han Sung Yeon Sarah, Barton-Owen Giles, Farrag Lynn, Bell Emily, Friend Lauren V, Ozcan Sureyya, Rustogi Nitin, Preece Rhian L, Eljasz Pawel, Tomasik Jakub, Cowell Daniel, Bahn Sabine
Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom.
Psyomics Ltd, Cambridge, United Kingdom.
JMIR Res Protoc. 2020 Aug 10;9(8):e18453. doi: 10.2196/18453.
Mood disorders affect hundreds of millions of people worldwide, imposing a substantial medical and economic burden. Existing diagnostic methods for mood disorders often result in a delay until accurate diagnosis, exacerbating the challenges of these disorders. Advances in digital tools for psychiatry and understanding the biological basis of mood disorders offer the potential for novel diagnostic methods that facilitate early and accurate diagnosis of patients.
The Delta Trial was launched to develop an algorithm-based diagnostic aid combining symptom data and proteomic biomarkers to reduce the misdiagnosis of bipolar disorder (BD) as a major depressive disorder (MDD) and achieve more accurate and earlier MDD diagnosis.
Participants for this ethically approved trial were recruited through the internet, mainly through Facebook advertising. Participants were then screened for eligibility, consented to participate, and completed an adaptive digital questionnaire that was designed and created for the trial on a purpose-built digital platform. A subset of these participants was selected to provide dried blood spot (DBS) samples and undertake a World Health Organization World Mental Health Composite International Diagnostic Interview (CIDI). Inclusion and exclusion criteria were chosen to maximize the safety of a trial population that was both relevant to the trial objectives and generalizable. To provide statistical power and validation sets for the primary and secondary objectives, 840 participants were required to complete the digital questionnaire, submit DBS samples, and undertake a CIDI.
The Delta Trial is now complete. More than 3200 participants completed the digital questionnaire, 924 of whom also submitted DBS samples and a CIDI, whereas a total of 1780 participants completed a 6-month follow-up questionnaire and 1542 completed a 12-month follow-up questionnaire. The analysis of the trial data is now underway.
If a diagnostic aid is able to improve the diagnosis of BD and MDD, it may enable earlier treatment for patients with mood disorders.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/18453.
情绪障碍影响着全球数亿人，带来了巨大的医疗和经济负担。现有的情绪障碍诊断方法往往导致准确诊断延迟，加剧了这些疾病带来的挑战。精神科数字工具的进步以及对情绪障碍生物学基础的理解为新型诊断方法提供了可能，这些方法有助于对患者进行早期准确诊断。
开展Delta试验以开发一种基于算法的诊断辅助工具，该工具结合症状数据和蛋白质组学生物标志物，以减少将双相情感障碍（BD）误诊为重度抑郁症（MDD）的情况，并实现更准确、更早的MDD诊断。
这项经伦理批准的试验的参与者通过互联网招募，主要是通过脸书广告。然后对参与者进行资格筛选，同意参与，并在专门构建的数字平台上完成一份为该试验设计和创建的适应性数字问卷。这些参与者中的一部分被选中提供干血斑（DBS）样本，并接受世界卫生组织世界心理健康综合国际诊断访谈（CIDI）。选择纳入和排除标准是为了在与试验目标相关且具有普遍性的试验人群中最大限度地提高安全性。为了为主要和次要目标提供统计效力和验证集，需要840名参与者完成数字问卷、提交DBS样本并接受CIDI。
Delta试验现已完成。超过3200名参与者完成了数字问卷，其中924人还提交了DBS样本和CIDI，而共有1780名参与者完成了6个月的随访问卷，1542人完成了12个月的随访问卷。目前正在对试验数据进行分析。
如果一种诊断辅助工具能够改善BD和MDD的诊断，它可能使情绪障碍患者能够更早接受治疗。
国际注册报告识别码（IRRID）：DERR1-10.2196/18453
