Prediction of SSRI Treatment in Major Depression.

NCT ID: NCT03670823

Last Updated: 2019-06-07

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

UNKNOWN

Total Enrollment

100 participants

Study Classification

OBSERVATIONAL

Study Start Date

2019-03-01

Study Completion Date

2020-10-01

Brief Summary

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This project will combine the data collected from EEG, Eye tracking, structural and functional MRI scans and neuropsychological performance from patients with major depression receiving SSRI treatment. The purpose of this research is to predict the success of the SSRI treatment and to categorize patients into sub-groups according to similar patterns of brain activation to personalize treatment.

Detailed Description

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Major depression is a mood disorder affecting 350 million people worldwide. The disorder is characterized by depressed mood, anhedonia, decreased quality of life, deficits in cognitive functions and even suicide thoughts. Treatment of depression is often a long process and includes taking different types and quantities of medications. Therefore, there is a need to predict the success of the SSRI treatment. Our research will examine the outcomes of the combined technologies: BNA (EEG), Eye-tracker, structural and functional MRI scans and neuropsychology tasks in patients with depression while receiving SSRI treatment. The purpose of the research is to track biomarkers and other measures, which will allow predicting the SSRI treatment's success within 4 weeks instead of 8 weeks. In addition, the investigators will attempt to categorize patients into different subgroups according to their brain activation and eye movements. This division into subgroups may contribute to the understanding of the mechanisms that account for the responsiveness to SSRI treatment and to the possibility of targeting patients with depression towards a particular treatment. From this research, the investigators aim to personalize the treatment of depression, make it more efficient and reduce the amount of time for the patient to reach an optimal responsiveness.

Conditions

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Major Depression

Study Design

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Observational Model Type

CASE_CONTROL

Study Time Perspective

PROSPECTIVE

Study Groups

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Healthy subjects

50 healthy subjects for a control group

SIEMENS PRISMA MRI

Intervention Type DEVICE

Collect data on brain activation from different methods

Patients with Major Depression

50 patients with major depression for a research group

SIEMENS PRISMA MRI

Intervention Type DEVICE

Collect data on brain activation from different methods

Interventions

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SIEMENS PRISMA MRI

Collect data on brain activation from different methods

Intervention Type DEVICE

Other Intervention Names

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BNA (EEG) Technology, Eyetracking device

Eligibility Criteria

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Inclusion Criteria

1. Patients 18-65 years old
2. Male and female
3. Ability to comprehend and sign informed consent
4. DSM-5 diagnosis with MINI 7.0.2 (healthy subjects need to be ruled out)


1. DSM-5 diagnosis
2. 0-2 failed treatments
3. Patients which will start SSRI treatment

Exclusion Criteria

1. unconsciousness
2. Pregnancy or nursing
3. Cardiovascular instability
4. Metabolic instability (water, electrolytes, sugar)
5. Fever or evidence of microbiological pollutant
6. Deafness or blindness
7. Schizophrenia
8. Addiction disorders
9. Eating disorders
10. Bi-polar disorder
11. Cognitive deficits
12. Start a new psychotherapy during the research
13. Unable to enter the MRI scanner
Minimum Eligible Age

18 Years

Maximum Eligible Age

65 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Sheba Medical Center

OTHER_GOV

Sponsor Role collaborator

Hebrew University of Jerusalem

OTHER

Sponsor Role collaborator

ElMindA Ltd

INDUSTRY

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Sheba Medical CENTER

Ramat Gan, , Israel

Site Status RECRUITING

Countries

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Israel

Central Contacts

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Revital Amiaz

Role: CONTACT

+972505250590

Liran Korine

Role: CONTACT

+972507453300

Facility Contacts

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Sarel Shlomo

Role: primary

03-5303075

References

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Drysdale AT, Grosenick L, Downar J, Dunlop K, Mansouri F, Meng Y, Fetcho RN, Zebley B, Oathes DJ, Etkin A, Schatzberg AF, Sudheimer K, Keller J, Mayberg HS, Gunning FM, Alexopoulos GS, Fox MD, Pascual-Leone A, Voss HU, Casey BJ, Dubin MJ, Liston C. Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat Med. 2017 Jan;23(1):28-38. doi: 10.1038/nm.4246. Epub 2016 Dec 5.

Reference Type BACKGROUND
PMID: 27918562 (View on PubMed)

Ogawa T, Sekino H, Uzura M, Sakamoto T, Taguchi Y, Yamaguchi Y, Hayashi T, Yamanaka I, Oohama N, Imaki S. Comparative study of magnetic resonance and CT scan imaging in cases of severe head injury. Acta Neurochir Suppl (Wien). 1992;55:8-10. doi: 10.1007/978-3-7091-9233-7_3.

Reference Type BACKGROUND
PMID: 1414552 (View on PubMed)

Raichle ME, Snyder AZ. A default mode of brain function: a brief history of an evolving idea. Neuroimage. 2007 Oct 1;37(4):1083-90; discussion 1097-9. doi: 10.1016/j.neuroimage.2007.02.041. Epub 2007 Mar 6.

Reference Type BACKGROUND
PMID: 17719799 (View on PubMed)

Rohden AI, Benchaya MC, Camargo RS, Moreira TC, Barros HMT, Ferigolo M. Dropout Prevalence and Associated Factors in Randomized Clinical Trials of Adolescents Treated for Depression: Systematic Review and Meta-analysis. Clin Ther. 2017 May;39(5):971-992.e4. doi: 10.1016/j.clinthera.2017.03.017. Epub 2017 May 2.

Reference Type BACKGROUND
PMID: 28476404 (View on PubMed)

Other Identifiers

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ELM-55 5323-18-SMC

Identifier Type: -

Identifier Source: org_study_id

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