NCT06773585: IRPA

Investigations of Factors Associated With Treatment Response and Prognosis in Anxiety Disorders

Not yet recruiting Last updated 30 April 2025

What this trial tests

trial testing Psychiatric scale assessments, VR-Based Behavioral Assessment, Brain MRI in Panic Disorder in 185 participants. Not yet recruiting.

Timeline

15 May 2025

Primary endpoint
15 May 2029

15 December 2029

Quick facts

Lead sponsor	Kangbuk Samsung Hospital
Status	Not yet recruiting
Study type	OBSERVATIONAL
Enrollment	185
Start date	15 May 2025
Primary completion	15 May 2029
Estimated completion	15 December 2029
Sites	1 location across South Korea

Drugs / interventions tested

• Psychiatric scale assessments, VR-Based Behavioral Assessment, Brain MRI

Conditions studied

• Panic Disorder — all drugs for Panic Disorder →

Sponsor

Kangbuk Samsung Hospital

Who can join

Adults 19 to 60, any sex, with Panic Disorder. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

The purpose of this study is to build a comprehensive brain and behavioral dataset on anxiety disorders and identify clinical factors related to treatment response and prognosis in patients with anxiety disorders. By conducting an integrated analysis of clinical features (phenotypes), comorbid conditions, virtual reality (VR)-based behavioral data, electroencephalogram (EEG) data, and MRI-based data in patients undergoing treatment for anxiety disorders and healthy controls, this study aims to enhance the understanding of the pathophysiology of anxiety disorders and establish a foundation for precision medicine.

Anxiety disorders significantly impair quality of life by inducing irrational fear and apprehension even in everyday situations. Over the past few years, the prevalence of anxiety disorders and associated medical expenses have surged, escalating the societal and economic burden. However, the current diagnostic system, DSM-5, relies on symptom-based approaches, which often lead to heterogeneity within the same diagnostic category. This limitation hinders the accurate prediction of treatment response and the design of optimal therapeutic strategies. To address these issues, the U.S. National Institute of Mental Health (NIMH) proposed the Research Domain Criteria (RDoC). RDoC is a multidimensional framework that integrates behavioral, psychological, and neurological data to facilitate the development of treatment strategies rooted in pathophysiology. Nonetheless, the acquisition of objective and reliable assessment data remains a challenge due to the inherent characteristics of mental disorders.

Virtual reality (VR) technology has emerged as a promising solution to overcome these limitations. VR enables the creation of immersive 3D environments that can elicit anxiety-related behaviors and precisely evaluate them in controlled settings. It also allows data collection in scenarios that closely resemble real-life situations while offering advantages such as repeatability and ease of use. Combining behavioral data collected in VR environments with EEG data can provide a more detailed understanding of the neurophysiological representations underlying anxiety behaviors. EEG, as a biomarker reflecting neural activity in real time, facilitates intuitive and effective analyses. Moreover, MRI-based brain imaging plays a critical role in identifying structural and functional connectivity differences between anxiety disorder patients and healthy controls. It offers crucial insights into the biomarkers that predict treatment outcomes and prognosis.

By integrating these data, this study seeks to uncover the key factors influencing treatment response and prognosis in patients with anxiety disorders.

Publications & conference data

1 peer-reviewed publication reference this trial (live from Europe PMC):

1. Identifying Neurobehavioral Biomarkers of Anxiety and Treatment Response Using Virtual Reality, Electroencephalography, Magnetic Resonance Imaging, and Related Multimodal Assessments: A Longitudinal Study Protocol.
   Oh H, Cha J, Kim BH, Oh KS, et al · · 2025 · PMID 41517257 · DOI 10.3390/jcm15010007