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

NCT ID: NCT06773585

Last Updated: 2025-04-30

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Total Enrollment

185 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-05-15

Study Completion Date

2029-12-15

Brief Summary

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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.

Detailed Description

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\[ Observational Parameters, Clinical and Laboratory Assessments \]

Participants in the anxiety behavior group will undergo four visits (initial evaluation, 2-month follow-up, 6-month follow-up, and 12-month follow-up), while the healthy control group will attend two visits (initial evaluation and 12-month follow-up). As the evaluations at 2 and 12 months consist solely of basic clinical assessments, they may be conducted via remote methods, such as telephone interviews or online surveys (e.g., Google Forms).

Initial Evaluation:

The initial evaluation includes approximately one hour of clinical and psychiatric symptom evaluations, a 30-minute virtual reality-based behavioral assessment, and a 40-minute brain imaging session.

1. Clinical assessment:

Includes the assessment of sociodemographic factors (e.g., gender, age, education level, marital status, occupation, alcohol and smoking habits, height, and weight) and anxiety disorder-related medical history (e.g., symptom patterns and duration, psychiatric treatment history, and family history).
2. Evaluation of anxiety symptoms and associated psychiatric conditions:

Utilizes various standardized scales and questionnaires, such as PDSS, LSAS, GAD, DASS, IUS, ASI, BAS, PANAS, neurocognitive tests, SSQ, and STRAIN.
3. Virtual Reality-Based Behavioral Assessment:

Gathers biometric signals and EEG data in response to stimuli presented in virtual environments.
4. Brain MRI:

Conducted using a 3.0T Philips Ingenia CX scanner, acquiring T1-weighted 3D coronal structural images, resting-state functional MRI, and diffusion-weighted images.

Follow-Up Assessments:

Participants in the anxiety behavior group will undergo assessments of four measures - PDSS, LSAS, GAD, and DASS - at 2 and 12 months. At 6 months, they will undergo assessments covering (2) the evaluation of anxiety symptoms and associated psychiatric characteristics, (3) virtual reality-based behavioral assessments, and (4) brain MRI, as conducted at baseline.

Healthy control participants will undergo the same four assessments (PDSS, LSAS, GAD, DASS) evaluating anxiety symptoms and associated psychiatric characteristics at 12 months at the Department of Psychiatry of our institution.

At 12 months, both the anxiety behavior group and the healthy control group will additionally complete the collection of clinical evaluation items (1), excluding sex and age.

\[ Data Analysis and Statistical Methods \] The results of the initial evaluation will be used to develop a three-group classification model (healthy controls vs. response vs. no-response) based on clinical evaluation outcomes at 2, 6, and 12 months. Participants will be categorized into remission and no-remission groups based on a ≥40% reduction in the PDSS score at the 2, 6, and 12 months follow-up assessments, allowing for a detailed understanding of the treatment effects over time.

Additionally, a regression model will be constructed to analyze the magnitude of changes in clinical evaluation outcomes.

This study will test various machine learning models, including classification methods like Dummy, Logistic Regression, Support Vector Machine, and Boosting models (eXtreme Gradient Boosting, CatBoost), using k-fold cross-validation to evaluate performance through accuracy, balanced accuracy, and F1 scores. Regression models, including Dummy Regressor, Linear Regression, Support Vector Regression, Multilayer Perceptron, and Bayesian Regression, will be assessed using Mean Squared Error (MSE), Mean Absolute Error (MAE), and R² scores.

The pathophysiology of anxiety disorder will be explored using resting-state functional brain MRI data, with cross-sectional and longitudinal comparisons of anxiety behavior groups and healthy controls. Network analysis will be conducted to identify significant brain connections, with false discovery rate (FDR) correction applied to control for multiple comparisons.

Conditions

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Panic Disorder

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Anxiety Behavior Group

Participants diagnosed with an anxiety disorder based on DSM-5 diagnostic criteria, evaluated by a board-certified psychiatrist. The principal investigator, a board-certified psychiatrist, will conduct the following diagnostic assessments and differential diagnoses to screen eligible participants according to the inclusion and exclusion criteria. Anxiety disorders will be diagnosed using the Structured Clinical Interview for DSM-5 Disorders, Clinical Version (SCID-5-CV; First et al., 2016), and other major psychiatric conditions will be ruled out using the Mini International Neuropsychiatric Interview (MINI; Lecrubier et al., 1997).

Participants will undergo four visits (initial evaluation, 2-month follow-up, 6-month follow-up, and 12-month follow-up).

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

Intervention Type DIAGNOSTIC_TEST

This study is a minimal-risk study involving non-invasive, non-pharmacological interventions. Participants will continue receiving their usual medication or counseling treatments as part of their routine care during the study.

When participants come to the hospital for assessments, they will engage in clinical assessments and complete questionnaires over a period of 1-2 hours, undergo MRI scans, and participate in virtual environment-based behavioral assessments. They will have the option to take breaks during the assessments and can withdraw from the study at any time without providing a reason.

Healthy Control Group

Individuals who report no psychiatric symptoms and are not taking any psychotropic medications.

Participants will undergo two visits (initial evaluation and 12-month follow-up).

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

Intervention Type DIAGNOSTIC_TEST

This study is a minimal-risk study involving non-invasive, non-pharmacological interventions. Participants will continue receiving their usual medication or counseling treatments as part of their routine care during the study.

When participants come to the hospital for assessments, they will engage in clinical assessments and complete questionnaires over a period of 1-2 hours, undergo MRI scans, and participate in virtual environment-based behavioral assessments. They will have the option to take breaks during the assessments and can withdraw from the study at any time without providing a reason.

Interventions

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

This study is a minimal-risk study involving non-invasive, non-pharmacological interventions. Participants will continue receiving their usual medication or counseling treatments as part of their routine care during the study.

When participants come to the hospital for assessments, they will engage in clinical assessments and complete questionnaires over a period of 1-2 hours, undergo MRI scans, and participate in virtual environment-based behavioral assessments. They will have the option to take breaks during the assessments and can withdraw from the study at any time without providing a reason.

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

1. Anxiety Behavior Group

* Adults aged 19-60 years.
* Diagnosed with an anxiety disorder based on DSM-5 diagnostic criteria, evaluated by a board-certified psychiatrist.
* Individuals who fully understand the study's purpose and process and provide informed consent.
2. Healthy Control Group

* Adults aged 19-60 years.
* Individuals who report no psychiatric symptoms and are not taking any psychotropic medications.
* Individuals who fully understand the study's purpose and process and provide informed consent.

Exclusion Criteria

1. Anxiety Behavior Group

* Individuals unable to read the consent form.
* Individuals with difficulty using virtual reality devices.
* Individuals with a history of epileptic seizures, brain injuries, or neurological disorders.
* Individuals with severe physical illnesses (e.g., cancer, tuberculosis, severe cardiovascular diseases).
* Individuals with substance or alcohol use disorders.
* Individuals with pacemakers or implanted metallic devices.
* Pregnant individuals or those in vulnerable environments, such as institutional employees.
2. Healthy Control Group

* Additionally, individuals with any current or past psychiatric disorders are excluded.
Minimum Eligible Age

19 Years

Maximum Eligible Age

60 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Kangbuk Samsung Hospital

OTHER

Sponsor Role lead

Responsible Party

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Kim Junhyung

Clinical Assistant Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Kangbuk Samsung Medical Center

Seoul, Jongno-gu, South Korea

Site Status

Countries

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South Korea

Central Contacts

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Junhyung Kim, Clinical Assistant Professor

Role: CONTACT

+82-2-2001-2431

Jeongyeon Woo, Clinical Research Coordinator

Role: CONTACT

+82-2-2001-1805

Facility Contacts

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Junhyung Kim, Clinical Assistant Professor

Role: primary

+82-2-2001-2431

Other Identifiers

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KBSMC IRB 2024-10-018-002

Identifier Type: -

Identifier Source: org_study_id

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