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Development and Application of Treatment Optimization Technology Based on Depression Diagnosis and Stratification Markers

Development and Application of Treatment Optimization Technology Based on Depression Diagnosis and Stratification Markers - Development and Application of Treatment Optimization Technology Based on Depression Diagnosis and Stratification Markers

Status
Recruiting
Phases
Unknown
Study type
Unknown
Source
JPRN
Registry ID
JPRN-UMIN000060084
Enrollment
Unknown
Registered
2025-12-26
Start date
2024-11-18
Completion date
Unknown
Last updated
2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Mental disorders and healthy control

Interventions

None listed

Sponsors

Keio University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Participants aged 20 years or older (both depressed and healthy) from the existing dataset, "Longitudinal MRI study to elucidate neural circuit mechanisms associated with remission and recovery in mood disorders (commonly known as the L/R study)."

Exclusion criteria

Exclusion criteria: This study is an analytical study using an existing dataset, and will exclude 1. cases with insufficient medical information 2. cases who have expressed their intention not to participate through the opt-out process described below

Design outcomes

Primary

MeasureTime frame
Primary Endpoints (and their measures/evaluation methods): Evaluate the diagnostic performance for depression in the L/R study and assess differences in treatment efficacy among standard therapies (pharmacotherapy, CBT, ECT, rTMS) for each depression subtype. Regarding diagnostic performance for depression, diagnostic indices will be calculated using pre-existing programs applied to data from depressed patients and healthy controls. Diagnostic performance will be evaluated using indices such as AUC of the ROC curve, sensitivity, specificity, and discrimination rate based on the diagnostic indices for both groups. For depression subtypes, pre-existing programs will also be used to classify depression patient data into subtypes. Subsequently, longitudinal treatment data will be used to evaluate treatment responsiveness for each subtype. Secondary evaluation items (and their metrics/evaluation methods): Since the characteristics of groups receiving each treatment intervention may differ, we will evaluate diagnostic metric values and subtype classification rates among standard treatments (pharmacotherapy, CBT, ECT, rTMS) in the L/R study. For the depression group, we will calculate diagnostic indicators and subtypes using the pre-established program. Comparing these across standard treatments (pharmacotherapy, CBT, ECT, rTMS) will clarify the characteristics of each group. Exploratory evaluation items (and their indicators/evaluation methods): We will explore the relationship between depression diagnostic indicators and depression subtypes, as well as the relationship between depression diagnostic indicators/subtypes and clinical characteristics.

Countries

Japan

Contacts

Public ContactJinichi Hirano

Keio University School of Medicine

hjinichi@keio.jp03-5363-3971

Outcome results

None listed

Source: JPRN (via WHO ICTRP) · Data processed: Jul 3, 2026