Depression, UnipolarLEARNNCT03847688
Machine Learning to Predict Clinical Response to TMS
An observational study of Depression, Unipolar, run by Brown University at 1 site in United States.
Trial summary
Major Depressive Disorder (MDD) is a common and debilitating illness. It affects a person's family and personal relationships, work, education, and life. It changes sleeping and eating habits and significantly impairs patients' general health. Read more about this study
- Who is it for?
- Ages 18 to 65 years
- Conditions the study is for
- Depression, Unipolar
- What is being tested?
- Transcranial Magnetic Stimulation
- Type of treatment
- Medical device
- How many people
- 35 participants
- Where
- 1 siteUnited States
- Study dates
- 22 Oct 2018to 18 Sep 2020
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 65 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Adult Veterans, of any sex, ages 18-65, with MDD will participate in the study at the Providence VAMC. The patients will be referred by their providers for standard neuromodulation treatment, as happens currently.
Who may be able to join
- diagnosis of MDD, assessed by the Structured Clinical Interview of DSM-5 (SCID)
- treatment-resistant, operationally defined as failure to achieve clinical remission (MADRS <7) remit following at least one antidepressant trial in the current major depressive episode.
- Symptoms must be of at least moderate severity (MADRS score >19)
- medications will be stable for at least six weeks prior to TMS, and there will be no dose changes unless medically necessary
Who cannot join
- Standard contraindications to TMS and EEG :
- metal in the head and neck
- history of serious head injury or loss of consciousness over 10 minutes
- dementia
- seizure history
- other serious neurological disorders
Show all 10Show fewer
- serious or unstable medical conditions that would affect EEG signal
- current severe substance use disorders (except for nicotine or caffeine)
- bipolar or psychotic-spectrum disorders (e.g., schizophrenia, schizoaffective disorder, etc.)
- Prior non-responders to TMS will also be excluded.
Trial locations and contacts
1 site in 1 country.
United States1 site
Providence VA Medical Center
Providence, Rhode Island, 02908
About this study
Official title: Machine Learning to Predict Clinical Response to Transcranial Magnetic Stimulation: A Resting-State Electroencephalography Study
Major Depressive Disorder (MDD) is a common and debilitating illness. It affects a person's family and personal relationships, work, education, and life. It changes sleeping and eating habits and significantly impairs patients' general health. The disorder affects Veterans more than the general population, both as an isolated illness and in conjunction with posttraumatic stress disorder (PTSD) and suicidality. Symptoms in a notable proportion of patients (~30%) do not respond to behavioral and pharmacological interventions, and new treatments are in great need. One such treatment, transcranial magnetic stimulation (TMS), has been cleared by Food and Drug Administration for treatment in MDD. TMS is effective in around 60% of patients with treatment-resistant MDD but is associated with significant financial and time burden. Further insights into the neurobiological effects of TMS and markers for functional recovery prediction and treatment progression are of great value.
The goal of this proposal is to use human electrophysiology (electroencephalography, hereafter EEG, in particular) and machine learning to predict treatment response in candidates for TMS treatment and also study TMS's mechanism of action. Doing so has several benefits for patients, as prediction of treatment helps providers in screening out the patients for whom TMS is ineffective and understanding the mechanism allows us to refine and individualize the treatment.
Read more
The investigators will recruit 35 patients with treatment-resistant MDD and record resting state EEG signal with a dense electrode array before and after a 6-week clinical course of TMS treatment. The investigators will use machine learning (Sparse regressions) to predict treatment outcome using functional connectivity (Coherence) maps derived from the EEG signal. The investigators also will use classifiers to track changes in functional connectivity through the course of treatment. Based on our preliminary data, the investigators hypothesize that weaker functional connectivity between prefrontal cortex (where the stimulation is delivered) and parietal/posterior midline sites predict better response to treatment and that TMS treatment will enhance these connections.
The data collected here would be used as a seed and preliminary data for future federal (NIH and the VA) career development awards which will focus on the use of EEG to better understand brain function and neuromodulation treatments.
- Conditions
- Depression, Unipolar
- Being tested
- Transcranial Magnetic Stimulation
- Keywords
- Transcranial Magnetic Stimulation, Electroencephalography, Machine Learning
- Medical subject headings
- Depressive Disorder
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Transcranial Magnetic StimulationDevice
Patient receive Transcranial Magnetic Stimulation for treatment resistant depression as part of their routine care.
| Study group | Role | What they receive |
|---|---|---|
| Treatment resistant Major Depressive Disorder | Not described Receives: Device: Transcranial Magnetic Stimulation |
What is being measured
The primary outcome is the main question the study is designed to answer.
Changes in functional connectivity maps (i.e., EEG coherence) in patients before and after clinical TMS
The investigators test the hypothesis that TMS modulates cortical networks in a predictable/reproducible way, by using machine learning algorithms (classifiers) to identify changes in post-treatment EEG functional connectivity (quantified by calculating EEG signal Coherence) at different frequency bands (Alpha, Beta, Delta, and Theta).
Measured: Clinical symptoms are assessed and the EEG signal is recorded twice within 2 weeks before the first treatment session, twice in the 2 weeks following the last treatment session (typically 36th session), and at 3 and 6-month following the last treatment.
Prediction of clinical outcomes based on pre-treatment EEG functional connectivity
The investigators will use baseline/pre-treatment cortical functional connectivity (quantified by calculating EEG signal Coherence), to predict clinical response to Transcranial Magnetic Stimulation treatment in patients with Major Depressive Disorder. The ability to predict the outcome would be assessed by calculating the coefficient of determination (R2).
Measured: Clinical symptoms are assessed and the EEG signal is recorded twice within 2 weeks before the first treatment session. The two recordings would be used to asses test-retest validity.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted20 Feb 2019
- Study start22 Oct 2018
- Primary completion18 Sep 2020 (estimated)
- Study completion18 Sep 2020 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Depression, UnipolarStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 35 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Brown University
- Sponsor type
- University, hospital or other
- Collaborators
- Providence VA Medical Center
- Responsible party
- Sponsor
- Investigators
- Amin Zand Vakili, MD, PhD, Principal investigator, Brown University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03847688
- Sponsor's protocol ID
- 1805002078
- Acronym
- LEARN
- Status last verified
- Feb 2019
- First submitted
- 29 Jan 2019
- Last updated
- 25 Feb 2019
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 25 Feb 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Machine Learning to Predict Clinical Response to Transcranial Magnetic Stimulation: A Resting-State Electroencephalography Study
- ClinicalTrials.gov ID
- NCT03847688
- Acronym / sponsor ID
- LEARN / 1805002078
- Conditions
- Depression, Unipolar
- Keywords
- Transcranial Magnetic Stimulation, Electroencephalography, Machine Learning
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 35 participants (estimated)
- Lead sponsor
- Brown UniversityUniversity, hospital or other
- Collaborators
- Providence VA Medical Center
- Study start
- 22 Oct 2018 (actual)
- Primary completion
- 18 Sep 2020 (estimated)
- Study completion
- 18 Sep 2020 (estimated)
- First posted
- 20 Feb 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Major Depressive Disorder (MDD) is a common and debilitating illness. It affects a person's family and personal relationships, work, education, and life. It changes sleeping and eating habits and significantly impairs patients' general health. The disorder affects Veterans more than the general population, both as an isolated illness and in conjunction with posttraumatic stress disorder (PTSD) and suicidality. Symptoms in a notable proportion of patients (~30%) do not respond to behavioral and pharmacological interventions, and new treatments are in great need. One such treatment, transcranial magnetic stimulation (TMS), has been cleared by Food and Drug Administration for treatment in MDD. TMS is effective in around 60% of patients with treatment-resistant MDD but is associated with significant financial and time burden. Further insights into the neurobiological effects of TMS and markers for functional recovery prediction and treatment progression are of great value.
The goal of this proposal is to use human electrophysiology (electroencephalography, hereafter EEG, in particular) and machine learning to predict treatment response in candidates for TMS treatment and also study TMS's mechanism of action. Doing so has several benefits for patients, as prediction of treatment helps providers in screening out the patients for whom TMS is ineffective and understanding the mechanism allows us to refine and individualize the treatment.
The investigators will recruit 35 patients with treatment-resistant MDD and record resting state EEG signal with a dense electrode array before and after a 6-week clinical course of TMS treatment. The investigators will use machine learning (Sparse regressions) to predict treatment outcome using functional connectivity (Coherence) maps derived from the EEG signal. The investigators also will use classifiers to track changes in functional connectivity through the course of treatment. Based on our preliminary data, the investigators hypothesize that weaker functional connectivity between prefrontal cortex (where the stimulation is delivered) and parietal/posterior midline sites predict better response to treatment and that TMS treatment will enhance these connections.
The data collected here would be used as a seed and preliminary data for future federal (NIH and the VA) career development awards which will focus on the use of EEG to better understand brain function and neuromodulation treatments.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Treatment resistant Major Depressive Disorder | – | Device: Transcranial Magnetic Stimulation |
Who may qualify
- Ages
- 18 to 65 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Adult Veterans, of any sex, ages 18-65, with MDD will participate in the study at the Providence VAMC. The patients will be referred by their providers for standard neuromodulation treatment, as happens currently.
Key inclusion criteria (4 listed)
- diagnosis of MDD, assessed by the Structured Clinical Interview of DSM-5 (SCID)
- treatment-resistant, operationally defined as failure to achieve clinical remission (MADRS <7) remit following at least one antidepressant trial in the current major depressive episode.
- Symptoms must be of at least moderate severity (MADRS score >19)
- medications will be stable for at least six weeks prior to TMS, and there will be no dose changes unless medically necessary
Key exclusion criteria (10 listed)
- Standard contraindications to TMS and EEG :
- metal in the head and neck
- history of serious head injury or loss of consciousness over 10 minutes
- dementia
- seizure history
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Transcranial Magnetic StimulationPatient receive Transcranial Magnetic Stimulation for treatment resistant depression as part of their routine care. | Device | Treatment resistant Major Depressive Disorder |
Primary outcome
Changes in functional connectivity maps (i.e., EEG coherence) in patients before and after clinical TMS
Time frame: Clinical symptoms are assessed and the EEG signal is recorded twice within 2 weeks before the first treatment session, twice in the 2 weeks following the last treatment session (typically 36th session), and at 3 and 6-month following the last treatment.
The investigators test the hypothesis that TMS modulates cortical networks in a predictable/reproducible way, by using machine learning algorithms (classifiers) to identify changes in post-treatment EEG functional connectivity (quantified by calculating EEG signal Coherence) at different frequency bands (Alpha, Beta, Delta, and Theta).
Prediction of clinical outcomes based on pre-treatment EEG functional connectivity
Time frame: Clinical symptoms are assessed and the EEG signal is recorded twice within 2 weeks before the first treatment session. The two recordings would be used to asses test-retest validity.
The investigators will use baseline/pre-treatment cortical functional connectivity (quantified by calculating EEG signal Coherence), to predict clinical response to Transcranial Magnetic Stimulation treatment in patients with Major Depressive Disorder. The ability to predict the outcome would be assessed by calculating the coefficient of determination (R2).
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 25 Feb 2019.
- Individual participant dataSharing planned: No
Related trials for Depression, Unipolar
RecruitingPhase 2
Double-blind, Placebo-controlled Study in Adults With Major Depressive Disorder
Major Depressive Disorder (MDD)
RecruitingPhase 2
A Study to Evaluate the Safety and Efficacy of ALKS 7290 as an Adjunctive Therapy to Antidepressants in Adult Participants With Major Depressive Disorder
Major Depressive Disorder (MDD)
Recruiting
rTMS to Target Neural Connectivity and Rumination in Treatment-Resistant Depression
Depression, Treatment Resistant
Recruiting
Digital Intervention for Physical Activity
Depression - Major Depressive Disorder, Anxiety
Recruiting
Ketogenic Diet and Neuromodulation in Treatment Resistant Depression
Major Depressive Disorder (MDD), Treatment Resistant Depression (TRD)
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Amin Zand Vakili, MD, PhD principal investigator
Brown University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Depression, Unipolar, run by Brown University at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 10 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 25 Feb 2019. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Changes in functional connectivity maps (i.e., EEG coherence) in patients before and after clinical TMS (time frame: Clinical symptoms are assessed and the EEG signal is recorded twice within 2 weeks before the first treatment session, twice in the 2 weeks following the last treatment session (typically 36th session), and at 3 and 6-month following the last treatment.). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 25 Feb 2019.