Prediction of SSRI Treatment in Major Depression.

Major Depression Clinical Trial

Official title:

A Combination of Innovative Technologies: EEG, Eye Tracking Device and fMRI in Order to Predict the Success of SSRI Treatment in Patients With Major Depression.

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT03670823
• Other study ID #: ELM-55 5323-18-SMC
• Status: Recruiting
• Start date: March 1, 2019
• Est. completion date: October 1, 2020

Study information

• Verified date: May 2019
• Source: ElMindA Ltd
• Contact: Revital Amiaz
• Phone: +972505250590
• Email: Revital.Amiaz[@]sheba.health.gov.il
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

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.

Description:

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 100
• Est. completion date: October 1, 2020
• Est. primary completion date: October 1, 2020
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years to 65 Years

Eligibility

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)

Inclusion Criteria for patients with depression:

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

Related Conditions & MeSH terms

• Depression
• Depressive Disorder
• Depressive Disorder, Major
• Major Depression

Intervention

Device:
• SIEMENS PRISMA MRI
Collect data on brain activation from different methods

Locations

Country	Name	City	State
Israel	Sheba Medical CENTER	Ramat Gan

Sponsors (3)

Lead Sponsor	Collaborator
ElMindA Ltd	Hebrew University of Jerusalem, Sheba Medical Center

Country where clinical trial is conducted

Israel, 

References & Publications (4)

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. Erratum in: Nat Med. 2017 Feb 7;23 (2):264. — View Citation

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. — View Citation

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. Epub 2007 Mar 6. Review. — View Citation

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. Review. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	EEG responses to cognitive tasks in combination with the Eye-tracker Device.	Categorize patients into subgroups according to combined measures of EEG and Eye	2 years
Secondary	Resting state connectivity analysis	Examine the difference in resting state connectivity between the groups.	2 years
Secondary	Examine correlations between the different methods	Examine correlations between the different methods EEG, Eye-tracking and fMRI	2 years
Secondary	EEG brain activation to cognitive tasks	Categorize patients into subgroups according to similar brain activity	2 years
Secondary	Eye-tracking tasks	Categorize patients into subgroups according to similar patterns of eye movements.	2 years
Secondary	Examine MRI structural changes	Compare structural changes between the groups (patients with depression, healthy subjects).	2 years
Secondary	Cognitive scores on CANTAB (computerized cognitive assessments)	Examine the difference in responses to different cognitive exams between the groups	2 years