Skip to content

Research on Individualized Efficacy Prediction of Antidepressants Based on Multi-timepoint and Multimodal Data

Research on Individualized Efficacy Prediction of Antidepressants Based on Multi-timepoint and Multimodal Data

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500102933
Enrollment
Unknown
Registered
2025-05-21
Start date
2025-06-01
Completion date
Unknown
Last updated
2025-05-26

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

Conditions

Major Depressive Disorder

Interventions

Observation group:None

Sponsors

Beijing Anding Hospital, Capital Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 65 Years

Inclusion criteria

Inclusion criteria: 1.Age between 18 and 65 years old, regardless of gender; 2. With education level of primary school or higher; 3.Meet the diagnostic criteria for depression in the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5), and the diagnosis is verified by M.I.N.I. 4.Either first episode or recurrence is acceptable, and the total score of HAMD-17 at baseline is >=17 points; 5.Have not received systematic treatment for this episode and plan to receive antidepressant drug treatment; 6. The subject himself/herself signs the informed consent form.

Exclusion criteria

Exclusion criteria: 1. History of bipolar disorder, schizophrenia, depressive episode with psychotic features, or schizoaffective disorder, or organic mental disorder 2.Refractory depression (history of failure of = 2 antidepressant drug treatments in the past); 3.Score of the suicide item in HAMD-17 = 3 points; 4.History of dementia and other neurological diseases that seriously affect cognitive function; 5.History of drug or alcohol dependence within the past 6 months; 6.Received electroconvulsive therapy (ECT) within 3 months before enrollment; 7.Concurrent use of mood stabilizers, antipsychotic drugs, and drugs for the treatment of somatic diseases that affect neuroelectrophysiological indicators; 8.Other situations that the researcher deems inappropriate for enrollment.

Design outcomes

Primary

MeasureTime frame
Prediction accuracy of the antidepressant efficacy prediction model;

Secondary

MeasureTime frame
Electrophysiological biomarkers that have predictive value for antidepressant efficacy;

Countries

China

Contacts

Public ContactLei Feng

Beijing Anding Hospital, Capital Medical University

flxlm@126.com+86 158 1091 0218

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026